《国际政治经济学》文献资料（Political Economy of Migration）Labor market competition and individual preferences over immigration policy

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LABOR MARKET COMPETITION AND INDIVIDUAL PREFERENCES OVER IMMIGRATION POLICY Kenneth F.Scheve and Matthew J.Slaughter* Abstract-This paper uses three years of individual-level data to analyze consider labor market competition when evaluating immi- the determinants of individual preferences over immigration policy in the United States.We have two main empirical results.First,less-skilled gration policy.I workers are significantly more likely to prefer limiting immigrant inflows In this paper,we provide new evidence on the determi- into the United States.Our finding suggests that,over the time horizons nants of individual immigration-policy preferences and on that are relevant to individuals when evaluating immigration policy, what these preferences imply about how economies absorb individuals think that the U.S.economy absorbs immigrant inflows at least partly by changing wages.Second,we find no evidence that the relation- immigrants.We use a direct measure of these preferences ship between skills and immigration opinions is stronger in high-immi- from the 1992,1994,and 1996 National Election Studies gration communities. (NES)surveys (Sapiro et al.,1998),which are extensive surveys of current political opinions based on an individual- level,stratified random sample of the U.S.population.Our I.Introduction direct measure is the responses of U.S.citizens to a question NDIVIDUAL preferences over immigration policy are an asking about the number of immigrants U.S.policy should Lessential input into any complete model of immigration permit.Building on the NES surveys,we construct an policymaking.To understand both the policies implemented individual-level data set identifying both stated immigra- as well as the accompanying political conflict,we need to tion-policy preferences and potential immigration exposure know who supports more-or less-restrictionist policies and through several channels.We then evaluate how these why.Preferences surely depend on a host of considerations. preferences vary with individual characteristics that alter- including political ideology,ethnic and racial identity,and native theories predict might matter. expectations about the economic impact of new immigrants. We have two main empirical results.First,less-skilled workers are significantly more likely to prefer limiting Among economic considerations,the anticipated effect of immigrant inflows into the United States.This result is immigration on wages is likely to play a key role,as current robust to several different econometric specifications that factor income is a major determinant of individual eco- account for determinants of policy preferences other than nomic welfare.Because current factor income depends skills.Our finding suggests that,over the time horizons that primarily on individual skill levels,there may be a signifi- are relevant to individuals when evaluating immigration cant link from skills to wages to immigration-policy pref- policy,individuals think the U.S.economy absorbs immi- erences. grant inflows at least partly by changing wages.Further. Different economic models,however,make contrasting they form policy opinions in accord with their interests as predictions about the nature of this link.In the Heckscher- labor force participants.These preferences are consistent Ohlin model of international trade,immigrants sometimes with a Heckscher-Ohlin trade model and with a factor- have no impact on native wages.Factor-proportions analy- proportions analysis labor model.Second,we find no evi- sis,a framework often used by labor economists researching dence that the relationship between skills and immigration immigration,predicts that immigrants pressure the wages of opinions is stronger in high-immigration communities. similarly skilled natives nationwide.Area analysis.an alter- These preferences are inconsistent with an area-analysis native framework in the labor literature,predicts that immi- labor model. grants pressure the wages of similarly skilled natives who Section II relates our work to the political-economy reside in gateway communities where immigrants settle.In literature on immigration.Section III presents alternative short,there is theoretical uncertainty about the wages- economic models of immigration-policy preferences.Sec- mediated link between skills and preferences in addition to tion IV discusses the data and our model specifications. the empirical uncertainty regarding whether individuals Section V presents the empirical results,and section VI concludes. Received for publication January 26,1999.Revision accepted for II.The Political Economy of Immigration Policy publication April 14,2000. *Yale University,and Dartmouth College and NBER,respectively. Previous research on the determinants of immigration For generous data assistance,we thank George Borjas and John Cocklin For helpful comments,we thank two anonymous referees and Jim Alt, policy in receiving countries has emphasized the variation Patty Anderson,Danny Blanchflower,Irene Bloemraad,George Borjas, in immigration politics across countries and over time Lawrence Broz,Gary Freeman,Jeffry Frieden,Alan Kessler,Alejandro (Joppke,1998;Kessler,1998;Perotti,1998:Money,1997: Poire,Dave Richardson,and seminar participants at Harvard University. For financial support,Scheve thanks the Center for Basic Research in the Social Sciences and the Weatherhead Center for International Affairs,and I The terms area analysis and factor-proportions analysis we borrow Slaughter thanks the Russell Sage Foundation. from Borjas et al.(1996). The Review of Economics and Statistics,February 2001,83(1):133-145 2001 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology This content downloaded from 202.120.14.193 on Mon,15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

LABOR MARKET COMPETITION AND INDIVIDUAL PREFERENCES OVER IMMIGRATION POLICY Kenneth F. Scheve and Matthew J. Slaughter* Abstract-This paper uses three years of individual-level data to analyze the determinants of individual preferences over immigration policy in the United States. We have two main empirical results. First, less-skilled workers are significantly more likely to prefer limiting immigrant inflows into the United States. Our finding suggests that, over the time horizons that are relevant to individuals when evaluating immigration policy, individuals think that the U.S. economy absorbs immigrant inflows at least partly by changing wages. Second, we find no evidence that the relationship between skills and immigration opinions is stronger in high-immigration communities. I. Introduction I NDIVIDUAL preferences over immigration policy are an essential input into any complete model of immigration policymaking. To understand both the policies implemented as well as the accompanying political conflict, we need to know who supports more- or less-restrictionist policies and why. Preferences surely depend on a host of considerations, including political ideology, ethnic and racial identity, and expectations about the economic impact of new immigrants. Among economic considerations, the anticipated effect of immigration on wages is likely to play a key role, as current factor income is a major determinant of individual economic welfare. Because current factor income depends primarily on individual skill levels, there may be a significant link from skills to wages to immigration-policy preferences. Different economic models, however, make contrasting predictions about the nature of this link. In the HeckscherOhlin model of international trade, immigrants sometimes have no impact on native wages. Factor-proportions analysis, a framework often used by labor economists researching immigration, predicts that immigrants pressure the wages of similarly skilled natives nationwide. Area analysis, an alternative framework in the labor literature, predicts that immigrants pressure the wages of similarly skilled natives who reside in gateway communities where immigrants settle. In short, there is theoretical uncertainty about the wagesmediated link between skills and preferences in addition to the empirical uncertainty regarding whether individuals consider labor market competition when evaluating immigration policy.' In this paper, we provide new evidence on the determinants of individual immigration-policy preferences and on what these preferences imply about how economies absorb immigrants. We use a direct measure of these preferences from the 1992, 1994, and 1996 National Election Studies (NES) surveys (Sapiro et al., 1998), which are extensive surveys of current political opinions based on an individuallevel, stratified random sample of the U.S. population. Our direct measure is the responses of U.S. citizens to a question asking about the number of immigrants U.S. policy should permit. Building on the NES surveys, we construct an individual-level data set identifying both stated immigration-policy preferences and potential immigration exposure through several channels. We then evaluate how these preferences vary with individual characteristics that alternative theories predict might matter. We have two main empirical results. First, less-skilled workers are significantly more likely to prefer limiting immigrant inflows into the United States. This result is robust to several different econometric specifications that account for determinants of policy preferences other than skills. Our finding suggests that, over the time horizons that are relevant to individuals when evaluating immigration policy, individuals think the U.S. economy absorbs immigrant inflows at least partly by changing wages. Further, they form policy opinions in accord with their interests as labor force participants. These preferences are consistent with a Heckscher-Ohlin trade model and with a factorproportions analysis labor model. Second, we find no evidence that the relationship between skills and immigration opinions is stronger in high-immigration communities. These preferences are inconsistent with an area-analysis labor model. Section II relates our work to the political-economy literature on immigration. Section III presents alternative economic models of immigration-policy preferences. Section IV discusses the data and our model specifications. Section V presents the empirical results, and section VI concludes. II. The Political Economy of Immigration Policy Previous research on the determinants of immigration policy in receiving countries has emphasized the variation in immigration politics across countries and over time (Joppke, 1998; Kessler, 1998; Perotti, 1998; Money, 1997; Received for publication January 26, 1999. Revision accepted for publication April 14, 2000. * Yale University, and Dartmouth College and NBER, respectively. For generous data assistance, we thank George Borjas and John Cocklin. For helpful comments, we thank two anonymous referees and Jim Alt, Patty Anderson, Danny Blanchflower, Irene Bloemraad, George Borjas, Lawrence Broz, Gary Freeman, Jeffry Frieden, Alan Kessler, Alejandro Poire, Dave Richardson, and seminar participants at Harvard University. For financial support, Scheve thanks the Center for Basic Research in the Social Sciences and the Weatherhead Center for International Affairs, and Slaughter thanks the Russell Sage Foundation. 1 The terms area analysis and factor-proportions analysis we borrow from Borjas et al. (1996). The Review of Economics and Statistics, February 2001, 83(1): 133-145 ? 2001 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology This content downloaded from 202.120.14.193 on Mon, 15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

134 THE REVIEW OF ECONOMICS AND STATISTICS Freeman,1992,1995).There is general agreement that tions tended to restrict immigration to maintain the relative systematic differences in policies across countries depend income of the less skilled.3 on varying political institutions,divergent national histories In contrast to the policy focus of Goldin and Timmer and of settlement and colonialism,and the different effects of a Williamson,Citrin et al.(1997)use individual-level survey changing international context.Moreover,it seems clear data to study the immigration-policy preferences of a cross that even within countries the character of immigration section of U.S.citizens.Controlling for a wide range of politics changes over time.For example,a country's interest factors that potentially shape preferences,they conclude groups can dominate the policymaking process during some "that personal economic circumstances play little role in periods,while,in other periods,partisan electoral competi- opinion formation"(p.858).Specifically,they find that tion is central.In contrast to this observed variation across labor market competition does not influence preferences. time and space,very little research has focused on the Using information from a national poll,Espenshade and distribution of individual preferences over immigration pol- Hempstead (1996)find some mixed evidence that less- icy.Who supports free movement?Who advocates further educated and lower-family-income individuals are more restrictions?We contend that only once these questions likely to support immigration restrictions.They interpret about preferences have been adequately answered can a this evidence as suggesting that people care about immigra- convincing account of cross-country and over-time varia- tion's labor market impacts on wages,employment,and work conditions. tion in policymaking be constructed. Accounts of individual preferences can usefully be di- All these studies provide valuable information on the economic determinants of immigration-policy preferences vided into economic and non-economic determinants.Non- and political action.Our work builds upon them in three economic factors include individual beliefs about civil important ways. rights and expectations regarding the cultural impact of First,our study uses a direct measure of individual immigrants.The civil-rights dimension of immigration- immigration-policy preferences.Some studies cited above policy preferences has both a nondiscrimination aspect as infer from observed political actions or policy outcomes well as a more straightforward "free movement of persons" something about immigration-policy preferences.These in- element.Individual policy preferences are also likely to direct-preference measures face the important limitation of depend both on the degree to which individuals think being endogenous outcomes of the interaction between immigrants change native culture and on the desirability of immigration-policy (and possibly other,for example,for- those changes. eign-policy)preferences and domestic political institutions Economic determinants are generally hypothesized to be Policy preferences and institutions together determine pol- a function of the aggregate costs and benefits of immigra- icy actions,so the mapping from preferences to actions is tion,the fiscal impact on the public sector,and the impact of not unambiguous.Scheve and Slaughter(2001)discuss this immigrants on native labor market returns.This last con- point further. sideration is arguably the most critical economic factor Second,our study draws heavily on the trade and labor influencing individual policy preferences,and it is often the economics literature on immigration to test properly for the most controversial factor as well.Consequently,it is the economic determinants of immigration preferences.We test main issue addressed in this paper.2 three alternative models of how immigration affects the In previous work,Goldin (1994)and Timmer and Wil- economic welfare of natives.In contrast,none of the related liamson(1998)present historical evidence on the potential studies explicitly lays out any models of immigration.In- impact of labor market outcomes on immigration policy. stead,they all simply assume that immigration hurts natives Goldin finds that House Representatives in 1915 were more via lower wages,unemployment,and other adverse out- likely to vote in favor of a literacy test to restrict immigrant comes.Many important issues have not been explored,such inflows the lower were wage increases from 1907 to 1915 in as whether immigration preferences are systematically dif- the Representatives'district cities.Goldin interprets this as ferent in gateway communities. indirect evidence that immigrants'pressure on native wages Third,our study uses measures of individual economic contributed to tighter immigration restrictions.Pooling five exposure to immigration that follow closely from economic countries from 1860 to 1930,Timmer and Williamson find theory.This issue applies most strongly to Citrin et al. that more-restrictionist immigration policies were signifi- (1997)and Espenshade and Hempstead (1996).Empirical cantly correlated with lower unskilled wages relative to labor economists commonly measure skills via educational average per capita income.They interpret this correlation as attainment or occupation classification;our empirical work evidence that countries with more-unequal income distribu- 3 Hanson and Spilimbergo (1999)analyze the impact of economic conditions in the United States and Mexico on a different aspect of 2 Borjas (1995)concludes that the main economic impact of U.S immigration policy:border enforcement and apprehensions.They find that immigration is on the distribution of income,not on its aggregate level. the Mexican(that is,not U.S.)purchasing power of U.S.nominal wages Borjas (1999)presents a comprehensive analysis of current U.S.immi- is strongly correlated with border apprehensions of illegal Mexican gration policy.See also Freidberg and Hunt(1995). immigrants This content downloaded from 202.120.14.193 on Mon,15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

134 THE REVIEW OF ECONOMICS AND STATISTICS Freeman, 1992, 1995). There is general agreement that systematic differences in policies across countries depend on varying political institutions, divergent national histories of settlement and colonialism, and the different effects of a changing international context. Moreover, it seems clear that even within countries the character of immigration politics changes over time. For example, a country's interest groups can dominate the policymaking process during some periods, while, in other periods, partisan electoral competition is central. In contrast to this observed variation across time and space, very little research has focused on the distribution of individual preferences over immigration policy. Who supports free movement? Who advocates further restrictions? We contend that only once these questions about preferences have been adequately answered can a convincing account of cross-country and over-time variation in policymaking be constructed. Accounts of individual preferences can usefully be divided into economic and non-economic determinants. Noneconomic factors include individual beliefs about civil rights and expectations regarding the cultural impact of immigrants. The civil-rights dimension of immigrationpolicy preferences has both a nondiscrimination aspect as well as a more straightforward "free movement of persons" element. Individual policy preferences are also likely to depend both on the degree to which individuals think immigrants change native culture and on the desirability of those changes. Economic determinants are generally hypothesized to be a function of the aggregate costs and benefits of immigration, the fiscal impact on the public sector, and the impact of immigrants on native labor market returns. This last consideration is arguably the most critical economic factor influencing individual policy preferences, and it is often the most controversial factor as well. Consequently, it is the main issue addressed in this paper.2 In previous work, Goldin (1994) and Timmer and Williamson (1998) present historical evidence on the potential impact of labor market outcomes on immigration policy. Goldin finds that House Representatives in 1915 were more likely to vote in favor of a literacy test to restrict immigrant inflows the lower were wage increases from 1907 to 1915 in the Representatives' district cities. Goldin interprets this as indirect evidence that immigrants' pressure on native wages contributed to tighter immigration restrictions. Pooling five countries from 1860 to 1930, Timmer and Williamson find that more-restrictionist immigration policies were significantly correlated with lower unskilled wages relative to average per capita income. They interpret this correlation as evidence that countries with more-unequal income distributions tended to restrict immigration to maintain the relative income of the less skilled.3 In contrast to the policy focus of Goldin and Timmer and Williamson, Citrin et al. (1997) use individual-level survey data to study the immigration-policy preferences of a cross section of U.S. citizens. Controlling for a wide range of factors that potentially shape preferences, they conclude "that personal economic circumstances play little role in opinion formation" (p. 858). Specifically, they find that labor market competition does not influence preferences. Using information from a national poll, Espenshade and Hempstead (1996) find some mixed evidence that lesseducated and lower-family-income individuals are more likely to support immigration restrictions. They interpret this evidence as suggesting that people care about immigration's labor market impacts on wages, employment, and work conditions. All these studies provide valuable information on the economic determinants of immigration-policy preferences and political action. Our work builds upon them in three important ways. First, our study uses a direct measure of individual immigration-policy preferences. Some studies cited above infer from observed political actions or policy outcomes something about immigration-policy preferences. These indirect-preference measures face the important limitation of being endogenous outcomes of the interaction between immigration-policy (and possibly other, for example, foreign-policy) preferences and domestic political institutions. Policy preferences and institutions together determine policy actions, so the mapping from preferences to actions is not unambiguous. Scheve and Slaughter (2001) discuss this point further. Second, our study draws heavily on the trade and labor economics literature on immigration to test properly for the economic determinants of immigration preferences. We test three alternative models of how immigration affects the economic welfare of natives. In contrast, none of the related studies explicitly lays out any models of immigration. Instead, they all simply assume that immigration hurts natives via lower wages, unemployment, and other adverse outcomes. Many important issues have not been explored, such as whether immigration preferences are systematically different in gateway communities. Third, our study uses measures of individual economic exposure to immigration that follow closely from economic theory. This issue applies most strongly to Citrin et al. (1997) and Espenshade and Hempstead (1996). Empirical labor economists commonly measure skills via educational attainment or occupation classification; our empirical work 2 Borjas (1995) concludes that the main economic impact of U.S. immigration is on the distribution of income, not on its aggregate level. Borjas (1999) presents a comprehensive analysis of current U.S. immigration policy. See also Freidberg and Hunt (1995). 3Hanson and Spilimbergo (1999) analyze the impact of economic conditions in the United States and Mexico on a different aspect of immigration policy: border enforcement and apprehensions. They find that the Mexican (that is, not U.S.) purchasing power of U.S. nominal wages is strongly correlated with border apprehensions of illegal Mexican immigrants. This content downloaded from 202.120.14.193 on Mon, 15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

LABOR MARKET COMPETITION AND INDIVIDUAL PREFERENCES OVER IMMIGRATION POLICY 135 uses both these measures.4 In contrast,Citrin et al.primarily to the supply of skills has become increasingly concentrated interpret educational attainment as a demographic variable in the lower educational categories"(p.6).We assume that rather than an economic factor.Although previous studies NES respondents are aware of these facts.> have justified this choice on the relationship between edu- Given these two assumptions,we think that the economic cation and tolerance,we demonstrate that education mea- determinants of an individual's immigration-policy prefer- sures labor market skills once other considerations (such as ences depend on how an immigration-induced shift in the gender and political ideology)are controlled for.Citrin et al. U.S.relative endowment towards less-skilled workers af- measure skills with income and with eight dichotomous fects that individual's factor income.To maintain focus on occupation variables.Only four of the eight cover working equilibrium wage determination,in all models we assume individuals,and these-white collar,pink collar,low-threat that wages are sufficiently flexible to ensure full employ- blue collar,and high-threat blue collar-are not defined or ment.This allows us to abstract from unemployment,both justified with reference to economic theory or evidence. equilibrium and frictional,although unemployment is con- Espenshade and Hempstead use dichotomous variables for sidered in our empirical work.To maintain focus on differ- educational attainment and family(not individual)income, ent skill groups,in all models we assume just two factors of with all specifications using both types of variables.Overall, production:skilled labor and unskilled labor.This keeps our these earlier studies use questionable skill measures,and analysis as simple as possible.6 they do not report specifications with single measures only, nor do they test the joint significance of all skill measures together.These uncertainties regarding measurement and A. The Heckscher-Ohlin Model specification suggest the need for further analysis. The Heckscher-Ohlin (HO)trade model usually makes two key assumptions.First,there is one national labor m. Economic Models of Immigration-Policy market for each factor.Thanks to sufficient mobility of Preferences natives (and immigrants upon arrival),there are no geo- graphically segmented "local"labor markets.The second To make the connection between individual economic key assumption is there are more tradable products(that is, interests and immigration-policy preferences,we focus on sectors)than primary factors of production,with products how immigration affects individual factor incomes.Differ- differentiated by their factor intensities.Multiple products ent economic models make contrasting predictions about are essential for establishing many fundamental trade-the- the nature of the link from immigration to factor incomes to ory results,such as comparative advantage. policy preferences,and this section briefly summarizes three With these assumptions,in equilibrium a country chooses models:the Heckscher-Ohlin trade model,the factor-pro- (via the decentralized optimization of firms)the output mix portions analysis model,and the area-analysis model. that maximizes national income subject to the constraints of Across all three models we make two important assump- world product prices,national factor supplies,and national tions.First,we assume that current factor income is a major determinant of people's economic well-being.Second,we technology.This output mix consists of both which products actually get produced as well as the quantities of production. assume that U.S.citizens think that current immigrant In turn,this output mix helps determine the country's inflows increase the relative supply of less-skilled workers. national factor prices.The general intuition is that the As will be seen below,although this assumption about the technology parameters and world price for each produced skill-mix effects of immigrants is not explicitly stated in the sector help determine national wages.In the standard case NES question about immigration preferences,this assump- tion clearly reflects the facts about U.S.immigration in wherein the country makes at least as many products as the recent decades.Borjas,Freeman,and Katz (1997)report number of primary factors,equilibrium wages are a function that"on average,immigrants have fewer years of schooling of just the world prices and technology parameters of the than natives-a difference that has grown over the past two produced sectors.These wages do not depend on the prices decades,as the mean years of schooling of the immigration and technology of the nonproduced sectors.They also do population increased less rapidly than the mean years of not depend directly on the level of endowments (only schooling of natives.As a result,the immigrant contribution 5This skills gap between immigrants and natives does not address other interesting facts about the distribution of skills among immigrants.For 4 For example,in the recent research on the rising U.S.skill premium, example,Borjas et al.(1997)show that the skill distribution of U.S. the two most commonly used measures of the skill premium have been the immigration has been somewhat bimodal at both the high-and low-skill relative wage between college graduates and high-school graduates and ends of the distribution. the relative wage between nonproduction workers and production workers 6 In the political-economy literature,some researchers analyze thethe- (in manufacturing only).See Katz and Murphy (1992)or Lawrence and ory of economic determinants of immigration-policy preferences.Ben- Slaughter (1993),for example.Berman,Bound,and Griliches (1994) habib (1996)considers a one-good model in which natives have different document for the United States that employment trends for this job endowments of capital.Kessler (1998)focuses on how trade and immi- classification measure track quite closely the employment trends measured gration affect native factor returns in standard trade models.Bilal,Grether by the white-collar/blue-collar job classification,which in turn closely and de Melo (1998)consider the case of a three-factor,two-household, reflects the college/high-school classification. two-country world. This content downloaded from 202.120.14.193 on Mon,15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

LABOR MARKET COMPETITION AND INDIVIDUAL PREFERENCES OVER IMMIGRATION POLICY 135 uses both these measures.4 In contrast, Citrin et al. primarily interpret educational attainment as a demographic variable rather than an economic factor. Although previous studies have justified this choice on the relationship between education and tolerance, we demonstrate that education measures labor market skills once other considerations (such as gender and political ideology) are controlled for. Citrin et al. measure skills with income and with eight dichotomous occupation variables. Only four of the eight cover working individuals, and these-white collar, pink collar, low-threat blue collar, and high-threat blue collar-are not defined or justified with reference to economic theory or evidence. Espenshade and Hempstead use dichotomous variables for educational attainment and family (not individual) income, with all specifications using both types of variables. Overall, these earlier studies use questionable skill measures, and they do not report specifications with single measures only, nor do they test the joint significance of all skill measures together. These uncertainties regarding measurement and specification suggest the need for further analysis. I[I. Economic Models of Immigration-Policy Preferences To make the connection between individual economiic interests and immigration-policy preferences, we focus on how immigration affects individual factor incomes. Different economic models make contrasting predictions about the nature of the link from immigration to factor incomes to policy preferences, and this section briefly summarizes three models: the Heckscher-Ohlin trade model, the factor-proportions analysis model, and the area-analysis model. Across all three models we make two important assumptions. First, we assume that current factor income is a major determinant of people's economic well-being. Second, we assume that U.S. citizens think that current immigrant inflows increase the relative supply of less-skilled workers. As will be seen below, although this assumption about the skill-mix effects of immigrants is not explicitly stated in the NES question about immigration preferences, this assumption clearly reflects the facts about U.S. immigration in recent decades. Borjas, Freeman, and Katz (1997) report that "on average, immigrants have fewer years of schooling than natives-a difference that has grown over the past two decades, as the mean years of schooling of the immigration population increased less rapidly than the mean years of schooling of natives. As a result, the immigrant contribution to the supply of skills has become increasingly concentrated in the lower educational categories" (p. 6). We assume that NES respondents are aware of these facts.5 Given these two assumptions, we think that the economic determinants of an individual's immigration-policy preferences depend on how an immigration-induced shift in the U.S. relative endowment towards less-skilled workers affects that individual's factor income. To maintain focus on equilibrium wage determination, in all models we assume that wages are sufficiently flexible to ensure full employment. This allows us to abstract from unemployment, both equilibrium and frictional, although unemployment is considered in our empirical work. To maintain focus on different skill groups, in all models we assume just two factors of production: skilled labor and unskilled labor. This keeps our analysis as simple as possible.6 A. The Heckscher-Ohlin Model The Heckscher-Ohlin (HO) trade model usually makes two key assumptions. First, there is one national labor market for each factor. Thanks to sufficient mobility of natives (and immigrants upon arrival), there are no geographically segmented "local" labor markets. The second key assumption is there are more tradable products (that is, sectors) than primary factors of production, with products differentiated by their factor intensities. Multiple products are essential for establishing many fundamental trade-theory results, such as comparative advantage. With these assumptions, in equilibrium a country chooses (via the decentralized optimization of firms) the output mix that maximizes national income subject to the constraints of world product prices, national factor supplies, and national technology. This output mix consists of both which products actually get produced as well as the quantities of production. In turn, this output mix helps determine the country's national factor prices. The general intuition is that the technology parameters and world price for each produced sector help determine national wages. In the standard case wherein the country makes at least as many products as the number of primary factors, equilibiium wages are a function of just the world prices and technology parameters of the produced sectors. These wages do not depend on the plices and technology of the nonproduced sectors. They also do not depend directly on the level of endowments (only 4For example, in the recent research on the rising U.S. skill premium, the two most commonly used measures of the skill premium have been the relative wage between college graduates and high-school graduates and the relative wage between nonproduction workers and production workers (in manufacturing only). See Katz and Murphy (1992) or Lawrence and Slaughter (1993), for example. Berman, Bound, and Griliches (1994) document for the United States that employment trends for this jobclassification measure track quite closely the employmentrends measured by the white-collar/blue-collar job classification, which in turn closely reflects the college/high-school classification. 5 This skills gap between immigrants and natives does not address other interesting facts about the distribution of skills among immigrants. For example, Borjas et al. (1997) show that the skill distribution of IJ.S. immigration has been somewhat bimodal at both the high- and low-skill ends of the distribution. 6 In the political-economy literature, some researchers analyze the theory of economic deteiminants of immnigration-policy preferences. Benhabib (1996) considers a one-good model in which natives have different endowments of capital. Kessler (1998) focuses on how trade and immigration affect native factor returns in standard trade models. Bilal, Grether, and de Melo (1998) consider the case of a three-factor, two-household, two-country world. This content downloaded from 202.120.14.193 on Mon, 15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

136 THE REVIEW OF ECONOMICS AND STATISTICS FIGURE 1.--LABOR MARKET EQUILIBRIUM:THE HECKSCHER-OHLIN MODEL of two products is made on each elastic part;accordingly, different relative wages prevail on each elastic part.On the RS RS' RSo downward-sloping portions,the country makes only one (WsNWu) product.Output-mix changes are not possible along these portions,and so immigrants must price themselves into employment by changing wages.Point Eo designates the (Wg/Wu)" initial labor-market equilibrium,with relative labor supply RS.and relative wages (w,/w)..Two immigration shocks are shown.The sufficiently small immigration shock shifts Eo RS to RS'.Relative wages do not change,as immigrants (Ws/Wu)o RD trigger Rybczynski output-mix effects with no product-price changes.The sufficiently large shock shifts RS to RS",and the country now produces a new set of products.As a result, the unskilled wage falls relative to the skilled wage (to (Qs/Qu) (w/w)");with fixed produce prices,this relative-wage Skilled labor is subscripted"s"and unskilled labor"n".The RS schedule is national relative supply, decline will be a real-wage decline as well.7 and the RD schedule is national relative demand. The HO model has different predictions about the link between skills and immigration-policy preferences.If indi- indirectly through the endowments'role in selecting the viduals think FPI holds,then there should be no link from product mix). skills to preferences.In this case,people evaluate immigra- Immigration's wage effects depend on the initial product tion based on other considerations.If individuals think that mix,on the size of the immigration shock,and on whether immigration triggers both output-mix and wage effects then the country is large or small (that is,on whether its product unskilled (skilled)workers nationwide should prefer poli- mix does or does not have any influence on world product cies that lower(raise)immigration inflows. prices).Consider the standard case in which the initial output mix is sufficiently diversified so that wages depend on just world prices and technology. B.The Factor-Proportions Analysis Model In this case,with sufficiently small shocks,the country Like the HO model,this model also assumes a national absorbs immigrants by changing its output mix as predicted labor market.The fundamental difference between the two by the Rybczynski theorem:the same products are pro- is that this model assumes a single aggregate output sector. duced,but output tends to increase (decrease)in the non- Under this assumption,there can be no output-mix changes skill-intensive (skill-intensive)sectors.Whether wages to help absorb immigrants.Accordingly,any immigration change depends on whether the country is big or small:if inflow affects national wages by the same logic described the country is small,world prices do not change,and thus above.Lower relative wages for unskilled workers induce there are no wage effects.Leamer and Levinsohn(1995) firms to hire relatively more of these workers.The greater call this insensitivity of national wages to changes in na- the immigrant inflow,the greater the resultant wage tional factor supplies the factor price insensitivity (FPI) changes.In the labor literature,studies using this framework theorem.If the country is large,wages do change:the include Borjas et al.(1996,1997),and these studies calcu- relative price of non skill-intensive products declines,which late immigration-induced shifts in national factor propor- tends to lower(raise)wages for unskilled (skilled)workers. tions and then infer the resulting national wage changes. With sufficiently large immigration shocks,national Figure 2 displays the national labor market for the factor- wages do change.Large-enough shocks induce the country proportions analysis world.Here,the relative labor demand to make a different set of products,which entails a different schedule slopes downward everywhere,with no portions set of world prices and technology parameters and thus where FPI holds.Initial relative labor supply is again given different wages.This absorption of large shocks via changes in both output mix and wages holds whether the country is 7 Three comments are necessary on figure 1.First,the relative-supply big or small:in either case,wage inequality rises.In the schedule is vertical under the assumption that all workers are sufficiently literature on U.S.immigration,Hanson and Slaughter willing to work that they price themselves into employment regardless of (2001)find immigration-related changes of output mix the going relative wage.Second,along the national demand schedule the country's output mix progresses according to sector factor intensities.The among U.S.states. likely output mixes are as follows.Along the leftmost branch of RD,the Figure 1 displays the national labor market for the case of country makes only the most non-skill-intensive product.Along the first a small HO country with three products.The distinguishing flat,it makes this product and the"middle"intensity product,switching to only the middle product along the middle downward-sloping branch.The feature is the shape of relative labor demand.It has two country picks up the most skill-intensive product as well along the second perfectly elastic portions,each of which corresponds to a flat;finally,along the rightmost branch,it makes only the skill-intensive range of endowments for which FPI holds.The national product.Third,underlying the downward-sloping portions of RD is the assumption of flexible production technologies with factor substitutability. output mix varies along the demand schedule.A different set With Leontief technology,these portions would be vertical. This content downloaded from 202.120.14.193 on Mon,15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

136 THE REVIEW OF ECONOMICS AND STATISTICS FIGURE 1.-LABOR MARKET EQUIBRIUM: THE HECKSCHER-OHLIN MODEL (Ws/Wu) RS" RS' RSo (WS/WU)' Eo (Ws/Wu)O RD (Qs/Qu) Skilled labor is subscripted "s" atid unskilled labor "u". The RS schedule is nationial relative supply, and the RD schedule is national relative demand. indirectly through the endowments' role in selecting the product mix). Immigration's wage effects depend on the initial product mix, on the size of the immigration shock, and on whether the country is large or small (that is, on whether its product mix does or does not have any influence on world product prices). Consider the standard case in which the initial output mix is sufficiently diversified so that wages depend on just world prices and technology. In this case, with sufficiently small shocks, the countly absorbs immigrants by changing its output mix as predicted by the Rybczynski theorem: the same products are produced, but output tends to increase (decrease) in the nonskill-intensive (sk:ill-intensive) sectors. Whether wages change depends on whether the country is big or small: if the country is small, world prices do not change, and thus there are no wage effects. Leamer and Levinsohn (1995) call this insensitivity of national wages to changes in national factor supplies the factor price insensitivity (FPI) theorem. If the country is large, wages do change: the relative price of non skill-intensive products declines, which tends to lower (raise) wages for unskilled (skilled) workers. With sufficiently large immigration shocks, national wages do change. Large-enough shocks induce the country to make a different set of products, which entails a different set of world prices and technology parameters and thus different wages. This absorption of large shocks via changes in both output mix and wages holds whether the country is big or small: in either case, wage inequality rises. In the literature on U.S. immigration, Hanson and Slaughter (2001) find immigration-related changes of output mix among U.S. states. Figure 1 displays the national labor market for the case of a small HO country with three products. The distinguishing feature is the shape of relative labor demand. It has two perfectly elastic portions, each of which corresponds to a range of endowments for which FPI holds. The national output mix varies along the demand schedule. A different set of two products is made on each elastic part; accordingly, different relative wages prevail on each elastic part. On the downward-sloping portions, the country makes only one product. Output-mix changes are not possible along these portions, and so immigrants must price themselves into employment by changing wages. Point Eo designates the initial labor-market equilibrium, with relative labor supply RS,, and relative wages (w/lwu),. Two immigration shocks are shown. The sufficiently small immigration shock shifts RS, to RS'. Relative wages do not change, as immigrants trigger Rybczynski output-mix effects with no product-price changes. The sufficiently large shock shifts RS0 to RS', and the country now produces a new set of products. As a result, the unskilled wage falls relative to the skilled wage (to (w5/wj)"); with fixed produce prices, this relative-wage decline will be a real-wage decline as well.7 The HO model has different predictions about the link between skills and immigration-policy preferences. If individuals think FPI holds, then there should be no link from skills to preferences. In this case, people evaluate immigration based on other considerations. If individuals think that immigration triggers both output-mix and wage effects then unskilled (skilled) workers nationwide should prefer policies that lower (raise) immigration inflows. B. The Factor-Proportions Analysis Model Like the HO model, this model also assumes a national labor market. The fundamental difference between the two is that this model assumes a single aggregate output sector. Under this assumption, there can be no output-mix changes to help absorb immigrants. Accordingly, any immigration inflow affects national wages by the same logic described above. Lower relative wages for unskilled workers induce firms to hire relatively more of these workers. The greater the immigrant inflow, the greater the resultant wage changes. In the labor literature, studies using this framework include Borjas et al. (1996, 1997), and these studies calculate immigration-induced shifts in national factor proportions and then infer the resulting national wage changes. Figure 2 displays the national labor market for the factorproportions analysis world. Here, the relative labor demand schedule slopes downward everywhere, with no portions where FPI holds. Initial relative labor supply is again given 7 Three comments are necessary on figure 1. First, the relative-supply schedule is vertical under the assumption that all workers are sufficiently willing to work that they price themselves into employment regardless of the going relative wage. Second, along the national demand schedule the country's output mix progresses according to sector factor intensities. The likely output mixes are as follows. Along the leftmost branch of RD, the country makes only the most non-skill-intensive product. Along the first flat, it makes this product and the "middle" intensity product, switching to only the middle product along the middle downward-sloping branch. The country picks up the most skill-intensive product as well along the second flat; finally, along the rightmost branch, it makes only the skill-intensive product. Third, underlying the downward-sloping portions of RD is the assumption of flexible production technologies with factor substitutability. With Leontief technology, these portions would be vertical. This content downloaded from 202.120.14.193 on Mon, 15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

LABOR MARKET COMPETITION AND INDIVIDUAL PREFERENCES OVER IMMIGRATION POLICY 137 FIGURE 2.-LABOR MARKET EQUILIBRIUM:THE FACTOR-PROPORTIONS studies of immigration-Card (1990),Altonji and Card ANALYSIS MODEL OR THE AREA-ANALYSIS MODEL (1991),Butcher and Card (1991),LaLonde and Topel (Ws/Wu) (1991),and Goldin (1994)-that have tested for correlations RS RSo between immigrant flows into local labor markets and local native wages. (Ws/Wu) Graphically,the area-analysis model also looks like figure 2,but with the key difference that now this figure represents local and not national conditions.Here,immigration shifts only the local relative supply of labor and thus depresses only local unskilled wages.Given this,the area-analysis (Ws/Wu)o model predicts the following:unskilled (skilled)workers in RD gateway communities should prefer policies to lower(raise) immigration inflows.What about workers in nongateway communities?With no geographic labor mobility over time horizons relevant to individuals when evaluating immigra- (Qs/Qu) tion policy,there should be no correlation between these Skilled labor is subscripted"sand unskilled labor"The R.S schedule is relative supply.and the RD schedule is relative demand.For the factor- workers'skills and their preferences.More generally,with ngenioalhbornarketfortheaeanalysiEmodGL.trepecsadhseparaleloealhbormarkeL some labor mobility,workers in nongateway communities should have qualitatively similar preferences as do workers by the schedule RSo,with initial equilibrium again at E and in gateway communities,but the skills-preferences link (w,/w).Immigration shifts the supply schedule back to should be stronger among the gateway workers. RS',and the national skill premium rises to (w/w)'. Again,for fixed product prices,real wages change,too. IV.Data Description and Empirical Specification This model makes a single prediction about the link from skills to immigration-policy preferences:unskilled(skilled) A.Data Description workers nationwide should prefer policies to lower (raise) immigration inflows.This prediction can also come from We measure immigration-policy preferences by re- the HO model without FPI.Accordingly,evidence of a link sponses to the following question asked in the 1992,1994, between skills and preferences is consistent with both mod- and 1996 NES surveys. els. "Do you think the number of immigrants from foreign countries who are permitted to come to the United C.The Area-Analysis Model States to live should be increased a little,increased a Like the previous model,the area-analysis model also lot,decreased a little,decreased a lot,or left the same assumes a single output sector.The fundamental difference as it is now?" between the two is that this model assumes distinct,geo- This question requires respondents to reveal their general graphically segmented labor markets within a country.This position on the proper direction for U.S.immigration policy. assumption is likely untrue in the very long run,but it may To apply our theory framework to this question,we assume be true over shorter time horizons thanks to frictions such as that respondents think that U.S.immigrant inflows increase information and transportation costs that people (both na-the relative supply of less-skilled workers.As we discussed, tives and immigrants upon arrival)must incur to move.U.S. this assumption clearly reflects the facts about U.S.immi- "local"labor markets are usually defined by states or met- gration in recent decades.Later,we revisit this assumption ropolitan areas.Each local market has its own equilibrium in our data analysis.We constructed the variable Immigra- wages determined by local supply and local demand. tion Opinion by coding responses with a range of 5 (for If there is literally no mobility among local labor markets, those individuals responding "decreased a lot")down to 1 immigrants'wage effects are concentrated entirely in the (for those responding"increased a lot").Thus,higher values gateway communities where they arrive:immigration low- of Immigration Opinion indicate preferences for more- ers(raises)wages for the unskilled(skilled).In contrast,in restrictive policy. a national labor market,immigrants'wage pressures spread beyond gateway communities.Natives can leave gateway 8 The 1992 NES survey asked other questions about immigration-related communities when immigrants arrive,immigrants can move topics that we do not analyze.For example,respondents were asked on to other communities,or natives can choose not to enter whether they think Asians or Hispanics "take jobs away from people already here."We do not focus on this question because it does not gateway communities as they may have planned.In cases explicitly address immigration policy.Moreover,its responses cannot between these two extremes,immigrants affect wages ev- clearly distinguish among our three competing economic models.All our erywhere but to a greater extent in gateway labor markets. models assume full employment,so no natives could have jobs perma- nently"taken away"from immigrants.Moreover,our models are silent on The area-studies framework has guided many empirical the dynamics of adjustment.All three models could have immigrants This content downloaded from 202.120.14.193 on Mon,15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

LABOR MARKET COMPETITION AND INDIVIDUAL PREFERENCES OVER IMMIGRATION POLICY 137 FIGURE 2.-LABOR MARKET EQUILIBRIUM: THE FACTOR-PROPORTIONS ANALYSIS MODEL OR THE AREA-ANALYSIS MODEL (WS/Wu) RS' RSo (Ws/Wu)A (WsVWu)o Eo RD (QsIQu) Skilled labor is subscripted "s" and unskilled labor "u". 'The RS schedule is relative supply, and the RD schedule is relative demand. For the factor-proportions analysis inodel, this picture represents the single national labor mnarket; for the area-analysis model, it represents each separate local labor market. by the schedule RS,, with initial equilibrium again at E0 and (w/lw1,),. Immigration shifts the supply schedule back to RS', and the national skill premium rises to (w/lw,1)'. Again, for fixed product prices, real wages change, too. This model makes a single prediction about the link from skills to immigration-policy preferences: unskilled (skilled) workers nationwide should prefer policies to lower (raise) immigration inflows. This prediction can also come from the HO model without FPI. Accordingly, evidence of a link between skills and preferences is consistent with both models. C. The Area-Analysis Model Like the previous model, the area-analysis model also assumes a single output sector. The fundamental difference between the two is that this model assumes distinct, geographically segmented labor markets within a country. This assumption is likely untrue in the very long run, but it may be true over shorter time horizons thanks to frictions such as information and transportation costs that people (both natives and immigrants upon arrival) must incur to move. U.S. "local" labor markets are usually defined by states or metropolitan areas. Each local market has its own equilibrium wages determined by local supply and local demand. If there is literally no mobility among local labor markets, immigrants' wage effects are concentrated entirely in the gateway communities where they arrive: immigration lowers (raises) wages for the unskilled (skilled). In contrast, in a national labor market, immigrants' wage pressures spread beyond gateway communities. Natives can leave gateway communities when immigrants arrive, immigrants can move on to other communities, or natives can choose not to enter gateway communities as they may have planned. In cases between these two extremes, immigrants affect wages everywhere but to a greater extent in gateway labor markets. The area-studies framework has guided many empirical studies of immigration-Card (1990), Altonji and Card (1991), Butcher and Card (1991), LaLonde and Topel (1991), and Goldin (1994)-that have tested for correlations between immigrant flows into local labor markets and local native wages. Graphically, the area-analysis model also looks like figure 2, but with the key difference that now this figure represents local and not national conditions. Here, immigration shifts only the local relative supply of labor and thus depresses only local unskilled wages. Given this, the area-analysis model predicts the following: unskilled (skilled) workers in gateway communities should prefer policies to lower (raise) immigration inflows. What about workers in nongateway communities? With no geographic labor mobility over time horizons relevant to individuals when evaluating immigration policy, there should be no correlation between these workers' skills and their preferences. More generally, with some labor mobility, workers in nongateway communities should have qualitatively similar preferences as do workers in gateway communities, but the skills-preferences link should be stronger among the gateway workers. IV. Data Description and Empirical Specification A. Data Description We measure immigration-policy preferences by responses to the following question asked in the 1992, 1994, and 1996 NES surveys. "Do you think the number of immigrants from foreign countries who are permitted to come to the United States to live should be increased a little, increased a lot, decreased a little, decreased a lot, or left the same as it is now?" This question requires respondents to reveal their general position on the proper direction for U.S. immigration policy. To apply our theory framework to this question, we assume that respondents think that U.S. immigrant inflows increase the relative supply of less-skilled workers. As we discussed, this assumption clearly reflects the facts about U.S. immigration in recent decades. Later, we revisit this assumption in our data analysis. We constructed the variable Immigration Opinion by coding responses with a range of 5 (for those individuals responding "decreased a lot") down to 1 (for those responding "increased a lot"). Thus, higher values of Immigration Opinion indicate preferences for morerestrictive policy.8 8 The 1992 NES survey asked other questions about immigration-related topics that we do not analyze. For example, respondents were asked whether they think Asians or Hispanics "take jobs away from people already here." We do not focus on this question because it does not explicitly address immigration policy. Moreover, its responses cannot clearly distinguish among our three competing economic models. All our models assume full employment, so no natives could have jobs permanently "taken away" from immigrants. Moreover, our models are silent on the dynamics of adjustment. All three models could have immigrants This content downloaded from 202.120.14.193 on Mon, 15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

138 THE REVIEW OF ECONOMICS AND STATISTICS Our theoretical framework hypothesizes that immigration the MSA/county-10%definition.Alternative measures are policy can affect individuals'factor income according to discussed in the robustness checks. their skill levels.To test whether skills are a key determinant We also constructed several measures of non-economic of immigration-policy preferences,for each individual we determinants of preferences.Following previous work in the construct two commonly used skill measures.First,respon- political-economy literature,we include the following mea- dents were asked to report their occupations coded accord- sures in our baseline analysis:gender,age,race,ethnicity, ing to the three-digit 1980 Census Occupation Code classi- personal immigrant status,party identification,and political fication.From the U.S.Department of Labor (1992,1994, ideology.Gender is a dichotomous variable equal to 1 for 1996)we obtained the 1992,1994,and 1996 U.S.average females.Age is a continuous variable.For race,we construct weekly wages for each three-digit occupation.Under the the dichotomous variable Black,which is equal to 1 if the assumption that the average market returns for a given respondent is African-American.For ethnicity,we construct occupation are determined primarily by the skills required the dichotomous variable Hispanic,which is equal to 1 if for that occupation,these average wages,called Occupation the individual self-identifies with a Hispanic ethnic group. Wage,measure respondents'skill levels.As a second skill Immigrant is a dichotomous variable equal to 1 if the measure,the NES survey also records the years of education respondent or his/her parents were immigrants into the completed by each respondent,Education Years.Educa- United States.Party Identification is a categorical variable tional attainment is another commonly used measure of ranging from1for“strong Democrat'”to7for“strong skills,so we use it as an alternative skills variable. Republican."Finally,Ideology is a categorical variable As discussed earlier,Citrin et al.(1997)primarily inter- ranging from 1 for“extremely liberal'”to7for“extremely pret educational attainment as a demographic variable rather conservative."In addition to these variables,for certain than a skills variable.Below,we present strong evidence specifications we included additional regressors which we discuss below. that education measures labor-market skills once other con- siderations such as gender and political ideology are con- B.Missing Data and Multiple Imputation trolled for.Also,our mapping of occupation categories into average occupation wages captures skills across occupa- Upon constructing the variables described in subsection tions much more accurately than do the occupation categor- IV A and combining them into individual-level data sets for ical variables in Citrin et al. each cross-sectional survey,we observed that there was a In addition to skill measures,we need measures of where significant amount of missing data.In each survey,some respondents live combined with information about gateway individuals did not report either occupation or educational communities.For each respondent,the NES reports the attainment;thus,for these respondents,we could not con- county,state,and (where appropriate)metropolitan statisti- struct skill measures.Missing data also existed for some of cal area(MSA)of residence.We combine this information our non-economic determinants of immigration-policy pref- with immigration data to construct several alternative mea- erences.Across the range of models that we estimated, sures of residence in a high-immigration area.First,we when we simply dropped observations with any missing defined local labor markets two ways:by a combination of data,we generally lost between 25%and 45%of the total observations. MSAs and counties,and by states.In our MSA/county definition,each MSA (with all its constituent cities and This standard approach for dealing with missing values, known as listwise deletion,can create two major problems. counties)is a separate labor market;for individuals living One is inefficiency caused by throwing away information outside an MSA,the labor market is the county of residence. that is relevant to the statistical inferences being made. Following the extensive use of MSAs in area-analysis Furthermore,inferences from listwise-deletion estimation studies and Bartel's (1989)finding that immigrants arrive can be biased if the observed data differs systematically mostly into cities,we prefer the MSA/county definition but from the unobserved data.In our case,inefficiency was try states for robustness.Second,for each definition of local clearly a problem.We also had little reason to think our data labor markets,we try three different definitions of a high- were missing at random,so we worried about biased infer- immigration labor market:5%,10%,and 20%shares of ences.(See King et al.(2001)for a detailed discussion.) immigrants in the local population.These immigration and Alternatives to listwise deletion for dealing with missing labor force data are from the 1990 decennial census as data have been developed in recent years.The most general reported by the U.S.Bureau of the Census (1994).Alto- and extensively researched approach is multiple imputation gether,for each of our six primary measures,we construct a dichotomous variable,High Immigration MSA,which is In 1990,immigrants accounted for 7.9%of the overall U.S.population. equal to 1 for residents in high-immigration labor markets. Accordingly,our 5%cutoff might seem too low,but for completeness we In the tables,we report the results for our preferred measure, estimated the specification.Also,the 1990 Census MSA data are orga- nized by 1990 MSA definitions,but the 1992 and 1994 NES surveys locate individuals by 1980 MSA definitions.Using unpublished informa- "taking"jobs from natives during adjustment to a new full-employment tion on 1980-1990 MSA changes obtained from Census officials,we equilibrium. corrected discrepancies as best we could. This content downloaded from 202.120.14.193 on Mon,15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

138 THE REVIEW OF ECONOMICS AND STATISTICS Our theoretical framework hypothesizes that immigration policy can affect individuals' factor income according to their skill levels. To test whether skills are a key determinant of immigration-policy preferences, for each individual we construct two commonly used skill measures. First, respondents were asked to report their occupations coded according to the three-digit 1980 Census Occupation Code classification. From the U.S. Department of Labor (1992, 1994, 1996) we obtained the 1992, 1994, and 1996 U.S. average weekly wages for each three-digit occupation. Under the assumption that the average market returns for a given occupation are determined primarily by the skills required for that occupation, these average wages, called Occupation Wage, measure respondents' skill levels. As a second skill measure, the NES survey also records the years of education completed by each respondent, Education Years. Educational attainment is another commonly used measure of skills, so we use it as an altermative skills variable. As discussed earlier, Citrin et al. (1997) primarily interpret educational attainment as a demographic variable rather than a skills variable. Below, we present strong evidence that education measures labor-market skills once other considerations such as gender and political ideology are controlled for. Also, our mapping of occupation categories into average occupation wages captures skills across occupations much more accurately than do the occupation categorical variables in Citlin et al. In addition to skill measures, we need measures of where respondents live combined with information about gateway communities. For each respondent, the NES reports the county, state, and (where appropliate) metropolitan statistical area (MSA) of residence. We combine this information with immigration data to construct several alternative measures of residence in a high-immigration area. First, we defined local labor markets two ways: by a combination of MSAs and counties, and by states. In our MSA/county definition, each MSA (with all its constituent cities and counties) is a separate labor market; for individuals living outside an MSA, the labor market is the county of residence. Following the extensive use of MSAs in area-analysis studies and Bartel's (1989) finding that immigrants arrive mostly into cities, we prefer the MSA/county definition but try states for robustness. Second, for each definition of local labor markets, we try three different definitions of a highimmigration labor market: 5%, 10%, and 20% shares of immigrants in the local population. These immigration and labor force data are from the 1990 decennial census as reported by the IJ.S. Bureau of the Census (1994). Altogether, for each of our six primary measures, we construct a dichotomous variable, High Immigration MSA, which is equal to 1 for residents in high-immigration labor markets. In the tables, we report the results for our preferred measure, the MSA/county-10% definition. Alternative measures are discussed in the robustness checks.9 We also constructed several measures of non-economic determinants of preferences. Following previous work in the political-economy literature, we include the following measures in our baseline analysis: gender, age, race, ethnicity, personal immigrant status, party identification, and political ideology. Gender is a dichotomous variable equal to 1 for females. Age is a continuous variable. For race, we construct the dichotomous variable Black, which is equal to 1 if the respondent is African-American. For ethnicity, we construct the dichotomous variable Hispanic, which is equal to 1 if the individual self-identifies with a Hispanic ethnic group. Immigrant is a dichotomous variable equal to 1 if the respondent or his/her parents were immigrants into the United States. Party Identification is a categorical variable ranging from 1 for "strong Democrat" to 7 for "strong Republican." Finally, Ideology is a categorical variable ranging from 1 for "extremely liberal" to 7 for "extremely conservative." In addition to these variables, for certain specifications we included additional regressors which we discuss below. B. Missing Data and Multiple Imputation Upon constructing the variables described in subsection IV A and combining them into individual-level data sets for each cross-sectional survey, we observed that there was a significant amount of missing data. In each survey, some individuals did not report either occupation or educational attainment; thus, for these respondents, we could not construct skill measures. Missing data also existed for some of our non-economic determinants of immigration-policy preferences. Across the range of models that we estimated, when we simply dropped observations with any missing data, we generally lost between 25% and 45% of the total observations. This standard approach for dealing with missing values, known as listwise deletion, can create two major problems. One is inefficiency caused by throwing away information that is relevant to the statistical inferences being made. Furthermore, inferences from listwise-deletion estimation can be biased if the observed data differs systematically from the unobserved data. In our case, inefficiency was clearly a problem. We also had little reason to think our data were missing at random, so we worried about biased inferences. (See King et al. (2001) for a detailed discussion.) Alternatives to listwise deletion for dealing with missing data have been developed in recent years. The most general and extensively researched approach is multiple imputation "taking" jobs from natives during adjustment to a new full-employment equilibrium. 9 In 1990, immigrants accounted for 7.9% of the overall U.S. population. Accordingly, our 5% cutoff might seem too low, but for completeness we estimated the specification. Also, the 1990 Census MSA data are organized by 1990 MSA definitions, but the 1992 and 1994 NES surveys locate individuals by 1980 MSA definitions. Using unpublished information on 1980-1990 MSA changes obtained from Census officials, we corrected discrepancies as best we could. This content downloaded from 202.120.14.193 on Mon, 15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

LABOR MARKET COMPETITION AND INDIVIDUAL PREFERENCES OVER IMMIGRATION POLICY 139 (King et al.,2001;Schafer,1997;Little Rubin,1987; TABLE 1.-SUMMARY STATISTICS Rubin,1987).Multiple imputation makes a much weaker Variable 1992 1994 1996 assumption than does listwise deletion about the process Immigration Opinion 3.595 3.982 3.785 generating the missing data.Rather than assuming that the (1.027) (1.064) (0.982) unobserved data is missing completely at random,multiple Occupation Wage 0.512 0.574 0.601 imputation is consistent and gives correct uncertainty esti- (0.187) (0.227) (0.225) Education Years 12.923 13.153 13.328 mates if the data are missing randomly conditional on the (2.815) (2.637) (2.660) data included in the imputation procedures.The approach Gender 0.534 0.534 0.552 has several variations but always involves three main steps. (0.499) (0.499) (0.497) Age 45.755 46.264 47.544 First,some algorithm is used to impute values for the (17.711) (17.646) (17.416) missing data.In this step,m(m>1)"complete"data sets Black 0.129 0.115 0.122 are created consisting of all the observed data and imputa- (0.336 (0.319) (0.327) Hispanic 0.072 0.046 0.087 tions for the missing values.The second step simply in- (0.259) (0.209) (0.282) volves analyzing each of the m data sets using standard Immigrant 0.181 0.166 0.147 complete-data statistical methods.The final step combines (0.385) (0.371) (0.355) Party ID 3.701 3.916 3.673 the parameter estimates and variances from the m complete- (2.027) 2.102) (2.102) data analyses to form a single set of parameter estimates and Ideology 4.237 4.446 4.275 variances.Importantly,this step systematically accounts for (1.399) (1.348) (1.398) High Immigration MSA 0.235 0.227 0.215 variation across the m analyses due to missing data in (0.424) (0.419) (0.411) addition to ordinary sample variation. Number of observations 1795 The first step in our multiple-imputation procedures was 2485 1714 to create imputations in the missing data cells for all the Thesesmmary statisticsare multiple-imputaionsimates based on the ten imputed data setsfor each year.Each cell reports the variable mean and (in parenthesis)its standard deviation.Occipcrrlon Wige variables discussed in subsection IV A.We based our reports the actual weekly wage divided by 1000. imputations for the 1992,1994,and 1996 data on 36,28, and 26 variables selected,respectively,from each NES nonimputed information;they differ only in the imputations survey.These variables included all those used in our for missing data. analysis as well as additional information from each survey The second step in our multiple-imputation analysis was that we determined would be helpful in predicting the to run various ordered-probit models separately on each of missing data.10 Altogether,we imputed ten complete indi- the ten final data sets for each survey year.The last multiple- vidual-level data sets for each year.The exact imputation imputation step was to combine the ten sets of estimation algorithm we used is known by the acronym EMis because results for each specification to obtain a single set of to generate imputations it combines a well-known expecta- estimated parameter means and variances.The single set of tion-maximization missing-data algorithm with a round of estimated means is simply the arithmetic average of the ten importance sampling.King et al.(2001)provide a complete different estimation results.The single set of estimated explanation of the use of this algorithm for missing data variances is more complicated than a simple average be- problems.12 The final data sets for each year contain com- cause,as mentioned above,these variances account for both pleted observations equal to the actual number of individ- the ordinary within-sample variation and the between-sam- uals in each NES survey.Also,all data sets contain the same ple variation due to missing data.See King et al.(2001)and Schafer (1997)for a complete description of these vari- i0 For 1992,the variables included in the imputation model were ances. Immigration Opinion,Occupation Wage,Education Years,Gender,Age, Table 1 reports the summary statistics of our immigra- Black,Hispanic,Immigrant,Party ID,Ideology,High Immigration MSA. interactions of High Immigration MSA with skill measures,a continuous tion-opinion measure and explanatory variables calculated measure of percent immigrant in MSA/county of respondent,feeling by pooling together all ten of the imputed data sets for each thermometer scores for Hispanics and immigrants.family income,home year.The average value for Immigration Opinion was 3.60 ownership,union membership,retrospective evaluation of the national economy,retrospective evaluation of respondent's personal finances,three in 1992.3.98 in 1994,and 3.79 in 1996.The values reflect measures of respondent's tolerance,three responses to questions about the responses between "left the same as it is now"and "de- impact of Hispanic immigration on the United States,three responses to creased a little."13 questions about the impact of Asian immigration on the United States,the respondent's view of welfare restrictions for immigrants,three measures of the skill composition of immigrants in the respondent's geographical 13 For 1992,the exact breakdown of all responses to Immigration location,and a sample weighting variable.For 1994 and 1996,these same Opinion is as follows:58"increased a lot"(2.3%of the total sample,or variables,if available in the survey.were included.The variables for the 2.485):116 "increased a little"(4.7%).937 "left the same"(37.7%),552 imputation model were selected because they were included in the “decreased a little'”(22.2%),and505“decreased a lot'"(20.3%).In analysis models,were highly predictive of variables in the analysis model. addition,we imputed responses for the 87 people(3.5%)who responded or were highly predictive of the missingness in the data. "don't know/no answer"and the 230 people (9.3%)who were not asked The imputation procedures were implemented using Amelia:A Pro- the question because of survey design.(All results reported in the paper gram for Missing Data (Honaker et al.,1999). are robust to excluding these 230 observations from the analysis.)We also 12 In this analysis,the imputation model was multivariate normal with a note that the summary statistics in our data are similar to those obtained slight ridge prior. from the Current Population Survey(CPS).For example,in the 1992 CPS, This content downloaded from 202.120.14.193 on Mon,15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

LABOR MARKET COMPETITION AND INDIVIDUAL PREFERENCES OVER IMMIGRATION POLICY 139 (King et al., 2001; Schafer, 1997; Little & Rubin, 1987; Rubin, 1987). Multiple imputation makes a much weaker assumption than does listwise deletion about the process generating the missing data. Rather than assuming that the unobserved data is missing completely at random, multiple imputation is consistent and gives correct uncertainty estimates if the data are missing randomly conditional on the data included in the imputation procedures. The approach has several variations but always involves three main steps. First, some algorithm is used to impute values for the missing data. In this step, m(m > 1) "complete" data sets are created consisting of all the observed data and imputations for the missing values. The second step simply involves analyzing each of the m data sets using standard complete-data statistical methods. The final step combines the parameter estimates and variances from the m completedata analyses to form a single set of parameter estimates and variances. Importantly, this step systematically accounts for variation across the m analyses due to missing data in addition to ordinary sample variation. The first step in our multiple-imputation procedures was to create imputations in the missing data cells for all the variables discussed in subsection IV A. We based our imputations for the 1992, 1994, and 1996 data on 36, 28, and 26 variables selected, respectively, from each NES survey. These variables included all those used in our analysis as well as additional information from each survey that we determined would be helpful in predicting the missing data.10 Altogether, we imputed ten complete individual-level data sets for each year.1' The exact imputation algorithm we used is known by the acronym EMis because to generate imputations it combines a well-known expectation-maximization missing-data algorithm with a round of importance sampling. King et al. (2001) provide a complete explanation of the use of this algorithm for missing data problems.12 The final data sets for each year contain completed observations equal to the actual number of individuals in each NES survey. Also, all data sets contain the same nonimputed information; they differ only in the imputations for missing data. The second step in our multiple-imputation analysis was to run various ordered-probit models separately on each of the ten final data sets for each survey year. The last multipleimputation step was to combine the ten sets of estimation results for each specification to obtain a single set of estimated parameter means and variances. The single set of estimated means is simply the arithmetic average of the ten different estimation results. The single set of estimated variances is more complicated than a simple average because, as mentioned above, these variances account for both the ordinary within-sample variation and the between-sample variation due to missing data. See King et al. (2001) and Schafer (1997) for a complete description of these variances. Table 1 reports the summary statistics of our immigration-opinion measure and explanatory variables calculated by pooling together all ten of the imputed data sets for each year. The average value for Immigration Opinion was 3.60 in 1992, 3.98 in 1994, and 3.79 in 1996. The values reflect responses between "left the same as it is now" and "decreased a little." 13 TABLE 1 -SUMMARY STATISTICS Variable 1992 1994 1996 Immigration Opinion 3.595 3.982 3.785 (1.027) (1.064) (0.982) Occupation Wage 0.512 0.574 0.601 (0.187) (0.227) (0.225) Education Years 12.923 13.153 13.328 (2.815) (2.637) (2.660) Gender 0.534 0.534 0.552 (0.499) (0.499) (0.497) Age 45.755 46.264 47.544 (17.711) (17.646) (17.416) Black 0.129 0.115 0.122 (0.336) (0.319) (0.327) Hispanic 0.072 0.046 0.087 (0.259) (0.209) (0.282) Immigrant 0.181 0.166 0.147 (0.385) (0.371) (0.355) Party ID 3.701 3.916 3.673 (2.027) (2.102) (2.102) Ideology 4.237 4.446 4.275 (1.399) (1.348) (1.398) High Immigration MSA 0.235 0.227 0.215 (0.424) (0.419) (0.411) Number of observations 2485 1795 1714 These summary statistics are multiple-imputation estimates based on the ten imputed data sets for each year. Each cell reports the variable mean and (in parenthesis) its standard deviation. Occuipatiotn Wage reports the actual weekly wage divided by 1000. 10 For 1992, the variables included in the imputation model were Immigration Opinion, Occupation Wage, Education Years, Gender, Age, Black, Hispanic, Immigrant, Party ID, Ideology, High Immigration MSA, interactions of High Immigration MSA with skill measures, a continuous measure of percent immigrant in MSA/county of respondent, feeling thermometer scores for Hispanics and immigrants, family income, home ownership, union membership, retrospective evaluation of the national economy, retrospective evaluation of respondent's personal finances, three measures of respondent's tolerance, three responses to questions about the impact of Hispanic immigration on the United States, three responses to questions about the impact of Asian immigration on the United States, the respondent's view of welfare restrictions for immigrants, three measures of the skill composition of immigrants in the respondent's geographical location, and a sample weighting variable. For 1994 and 1996, these same variables, if available in the survey, were included. The variables for the imputation model were selected because they were included in the analysis models, were highly predictive of variables in the analysis model, or were highly predictive of the missingness in the data. 11 The imputation procedures were implemented using Amelia: A Program for Missing Data (Honaker et al., 1999). 12 In this analysis, the imputation model was multivariate normal with a slight ridge prior. 13 For 1992, the exact breakdown of all responses to Immigration Opinion is as follows: 58 "increased a lot" (2.3% of the total sample, or 2,485); 116 "increased a little" (4.7%), 937 "left the same" (37.7%), 552 "decreased a little" (22.2%), and 505 "decreased a lot" (20.3%). In addition, we imputed responses for the 87 people (3.5%) who responded "don't know/no answer" and the 230 people (9.3%) who were not asked the question because of survey design. (All results reported in the paper are robust to excluding these 230 observations from the analysis.) We also note that the summary stati.stics in our data are similar to those obtained from the Current Population Survey (CPS). For example, in the 1992 CPS, This content downloaded from 202.120.14.193 on Mon, 15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

140 THE REVIEW OF ECONOMICS AND STATISTICS TABLE 2.-DETERMINANTS OF IMMIGRATION-POLICY PREFERENCES:TESTING THE HECKSCHER-OHLIN AND FACTOR-PROPORTIONS ANALYSIS MODELS 1992 1994 1996 Regressor Model 1 Model 2 Model 1 Model 2 Model 1 Model 2 Occupation Wage -0.349 -0.811 -0.541 (0.130) (0.135) (0.133) Education Years -0.044 -0.074 -0.059 (0.010) (0.011) (0.012) Gender -0.022 -0.008 0.022 0.083 -0.020 0.024 (0.048) (0.046) (0.056) (0.054) (0.060) (0.057) Age -0.000 -0.002 0.000 -0.002 0.004 0.002 (0.001) (0.001) (0.002) (0.002) (0.002) (0.002) Black -0.207 -0.225 -0.222 -0.211 -0.238 -0.241 (0.080) (0.080) (0.091) (0.092 (0.096) (0.097) Hispanic -0.064 -0.122 -0.306 -0.360 -0.124 -0.172 (0.111) (0.110) (0.136 (0.137) (0.120) (0.121) Immigrant -0.158 -0.150 -0.213 -0.193 -0.220 -0.207 (0.066) (0.066) (0.076 (0.076 (0.087) (0.087) Party ID 0.003 0.008 -0.006 -0.002 -0.023 -0.016 (0.013) (0.013) (0.016 (0.016) (0.016) (0.016) Ideology 0.057 0.050 0.054 0.041 0.080 0.072 (0.020) (0.020) (0.028) (0.029) 0.025) (0.025) Number of observations 2485 2485 1795 1795 1714 1714 These results are multiple-imputation estimates of ordered-probit coefficients based on the ten imputed data sets for each year.Each cell reports the coefficient estimate and (in parenthesis)its standard error.In both models.the dependent variable is individual opinions regarding whether U.S.poliey should increase.decrease.or keep the same the annual number of legal immigrants.This variable is defined such that higher (lower)values indicate more estrictive fless-restrictive) policy prefe nces.For bre ed C.Econometric Model correlation is strongest in high-immigration labor markets. as hypothesized in the area-analysis model.To allow for any Our empirical work aims to test how skills and other factors affect the probability that an individual supports a differences across our three survey years,we estimate each cross section separately certain level of legal immigration.The level of immigration preferred by a respondent could theoretically take on any value,but we do not observe this level.We observe only V.Empirical Results whether or not the respondent chose one of five ordered categories.Because we have no strong reason to think,ex A. Testing How Skills Affect Immigration-Policy ante,that these five ordered categories are separated by Preferences equal intervals,a linear-regression model might produce Our initial specifications allow us to test the HO and biased estimates.The more appropriate model for this situ- factor-proportions analysis models.Table 2 presents the ation is an ordered probit which estimates not only a set of results for each year's full sample,where in model 1 we effect parameters but also an additional set of parameters measure skills with Occupation Wage and in model 2 we use representing the unobserved thresholds between categories. Education Years.The key message of table 2 is that,by In all our specifications,we estimate an ordered-probit either measure,skill levels are significantly correlated with model in which the expected mean of the unobserved Immigration Opinion atat least the 99%level.Less-skilled preferred immigration level is hypothesized to be a linear (more-skilled)individuals prefer more-restrictionist (less- function of the respondent's skills,a vector of demographic restrictionist)immigration policy.This skills-preferences identifiers,political orientation,and(perhaps)the immigra- link holds conditional on a large set of plausible non- tion concentration in the respondent's community.The key economic determinants of Immigration Opinion.Among hypothesis we want to evaluate is whether more-skilled these other regressors,Gender;Age,Hispanic,and Party individuals are less likely to support restrictionist immigra- Identification are mostly insignificantly different from zero. tion policies as predicted in the HO trade model and in the Black and Immigrant are mostly significantly negative: factor-proportions analysis model.Accordingly,in our base- blacks,and the group of immigrants plus children of immi- line specifications,we regress stated immigration-policy grants,prefer less-restrictionist immigration policy.Ideol- preferences on skills,demographic identifiers,and political ogy is significantly positive:more-conservative individuals orientation.In a second set of specifications,we also include prefer more-restrictionist immigration policy.Our nonskill a dummy variable indicating whether or not the respondent estimates are similar to those in Citrin et al.(1997)and lives in a high-immigration area and an interaction term Espenshade and Hempstead(1996).14 between this indicator and the respondent's skills.These second specifications test whether the skills-immigration 14 Appendix A table Al reports results for the table 2 specifications estimated on the listwise-deletion data sets for each year.The qualitative 52.2%of the sample was female,11.5%was black,and the average age results are similar to those discussed in the paper using multiple imputa- was43.3. tion.However,using conventional rules for inference,the statistical This content downloaded from 202.120.14.193 on Mon,15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

140 THE REVIEW OF ECONOMICS AND STATISTICS TABLE 2.-DETERMINANTS OF IMMIGRATION-POLICY PREFERENCES: TESTING THE HECKSCHER-OHLIN AND FACTOR-PROPORTIONS ANALYSIS MODELS 1992 1994 1996 Regressor Model 1 Model 2 Model 1 Model 2 Model 1 Model 2 Occupation Wage -0.349 -0.811 -0.541 (0.130) (0.135) (0.133) Education Years -0.044 -0.074 -0.059 (0.010) (0.011) (0.012) Gender -0.022 -0.008 0.022 0.083 -0.020 0.024 (0.048) (0.046) (0.056) (0.054) (0.060) (0.057) Age -0.000 -0.002 0.000 -0.002 0.004 0.002 (0.001) (0.001) (0.002) (0.002) (0.002) (0.002) Black -0.207 -0.225 -0.222 -0.211 -0.238 -0.241 (0.080) (0.080) (0.091) (0.092) (0.096) (0.097) Hispanic -0.064 -0.122 -0.306 -0.360 -0.124 -0.172 (0.111) (0.110) (0.136) (0.137) (0.120) (0.121) Immigrant -0.158 -0.150 -0.213 -0.193 -0.220 -0.207 (0.066) (0.066) (0.076) (0.076) (0.087) (0.087) Party ID 0.003 0.008 -0.006 -0.002 -0.023 -0.016 (0.013) (0.013) (0.016) (0.016) (0.016) (0.016) Ideology 0.057 0.050 0.054 0.041 0.080 0.072 (0.020) (0.020) (0.028) (0.029) (0.025) (0.025) Number of observations 2485 2485 1795 1795 1714 1714 These results are multiple-imputation estimates of ordered-probit coefficients based on the ten imputed data sets for each year. Each cell reports the coefficient estimate and (in parenthesis) its standard error. In both models, the dependent variable is individual opinions regarding whether U.S. policy should increase, decrease, or keep the same the annual number of legal immigrants. This variable is defined such that higher (lower) values indicate more-restrictive (less-restrictive) policy preferences. For brevity, estimated cut points are not reported. C. Econometric Model Our empirical work aims to test how skills and other factors affect the probability that an individual supports a certain level of legal immigration. The level of immigration preferred by a respondent could theoretically take on any value, but we do not observe this level. We observe only whether or not the respondent chose one of five ordered categories. Because we have no strong reason to think, ex ante, that these five ordered categories are separated by equal intervals, a linear-regression model might produce biased estimates. The more appropriate model for this situation is an ordered probit which estimates not only a set of effect parameters but also an additional set of parameters representing the unobserved thresholds between categories. In all our specifications, we estimate an ordered-probit model in which the expected mean of the unobserved preferred immigration level is hypothesized to be a linear function of the respondent's skills, a vector of demographic identifiers, political orientation, and (perhaps) the immigration concentration in the respondent's community. The key hypothesis we want to evaluate is whether more-skilled individuals are less likely to support restrictionist immigration policies as predicted in the HO trade model and in the factor-proportions analysis model. Accordingly, in our baseline specifications, we regress stated immigration-policy preferences on skills, demographic identifiers, and political orientation. In a second set of specifications, we also include a dummy variable indicating whether or not the respondent lives in a high-immigration area and an interaction term between this indicator and the respondent's skills. These second specifications test whether the skills-immigration correlation is strongest in high-immigration labor markets, as hypothesized in the area-analysis model. To allow for any differences across our three survey years, we estimate each cross section separately. V. Empirical Results A. Testing How Skills Affect Immigration-Policy Preferences Our initial specifications allow us to test the HO and factor-proportions analysis models. Table 2 presents the results for each year's full sample, where in model 1 we measure skills with Occupation Wage and in model 2 we use Education Years. The key message of table 2 is that, by either measure, skill levels are significantly correlated with Immigration Opinion at at least the 99% level. Less-skilled (more-skilled) individuals prefer more-restrictionist (lessrestrictionist) immigration policy. This skills-preferences link holds conditional on a large set of plausible noneconomic determinants of Immigration Opinion. Among these other regressors, Gender, Age, Hispanic, and Party Identification are mostly insignificantly different from zero. Black and Immigrant are mostly significantly negative: blacks, and the group of immigrants plus children of immigrants, prefer less-restrictionist immigration policy. Ideology is significantly positive: more-conservative individuals prefer more-restrictionist immigration policy. Our nonskill estimates are similar to those in Citrin et al. (1997) and Espenshade and Hempstead (1996).14 52.2% of the sample was female, 11.5% was black, and the average age was 43.3. 14 Appendix A table Al reports results for the table 2 specifications estimated on the listwise-deletion data sets for each year. The qualitative results are similar to those discussed in the paper using multiple imputation. However, using conventional rules for inference, the statistical This content downloaded from 202.120.14.193 on Mon, 15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

LABOR MARKET COMPETITION AND INDIVIDUAL PREFERENCES OVER IMMIGRATION POLICY 141 The actual coefficient estimates in table 2 identify the TABLE 3.-ESTIMATED EFFECT OF INCREASING SKILL LEVELS ON THE qualitative effect on Immigration Opinion of skills and our PROBABILITY OF SUPPORTING IMMIGRATION RESTRICTIONS other regressors.However,these coefficients do not answer Increase Skill Measure Change in Probability of From Mean to Supporting Immigration our key substantive question of how changes in skill levels Maximum Year Restrictions affect the probability that an individual supports immigra- Occupation Wage 1992 -0.086 tion restrictions.To answer this question,we used the (0.031) estimates of model 1 and 2 to conduct simulations that [-0.138,-0.036] Education Years -0.126 calculate the effect on immigration preferences of changing (0.029) skills,while holding the other variables constant at their [-0.174,-0.0811 sample means. Occupation Wage 1994 -0.337 (0.050) Our simulation procedure works as follows.Recognizing [-0.416,-0.252 that the parameters are estimated with uncertainty,we drew Education Years -0.112 1,000 simulated sets of parameters from their sampling (0.019) [-0.143,-0.081] distribution defined as a multivariate normal distribution Occupation Wage 1996 -0.201 with mean equal to the maximum-likelihood parameter (0.047) [-0.274,-0.120] estimates and variance equal to the variance-covariance Education Years -0.085 matrix of these estimates.For each of the 1,000 simulated (0.017) sets of coefficients,we then calculated two probabilities. [-0.113,-0.057 Setting all variables equal to their sample means,we first Using the estimates from model 1 and 2.we simulated the consequences of changing each skill measure from its mean to its maximum on the probability of supporting immigration restrictions.The calculated the estimated probability of supporting immigra- effect is 0% with the eoof this estimate in parentheses followed by tion restrictions (that is,the probability of supporting a reduction in immigration by either“alot”or“a little").We then calculated the estimated probability of supporting im- porting immigration restrictions.(Table A2 gives simulation migration restrictions when our skills measure is increased results for all variables in model 1 and 2).15 One possible objection to our analysis is the claim that to its sample maximum,while holding fixed all other re- Occupation Wage and Education Years measure labor-mar- gressors at their means.The difference between these two ket skills.For example,Education Years might indicate estimated probabilities is the estimated difference in the greater tolerance or civic awareness.To test this possibility, probability of supporting immigration restrictions between we split our sample between those in the labor force and an individual with average skills and someone with"max- those not in the labor force and then reestimated model 1 imum"skills.We calculated this difference 1,000 times,and and 2 on each subsample.We defined the subset of labor- then-to show the distribution of this difference-we cal-force participants as those individuals reporting that they culated its mean,its standard error,and a 90%-confidence were either employed or unemployed but seeking work.In interval around the mean. every year,the not-in-labor-force subsample was dispropor- Table 3 reports the results of this simulation for our two tionately female:approximately two females for every male, skills regressors.For 1992,increasing Occupation Wage versus a majority of males in the labor-force group.In every from its mean to its maximum($512 per week to $1138 per year,the not-in-labor-force subsample was also much older: week),holding fixed all other regressors at their means, an average age of approximately sixty versus forty for those reduces the probability of supporting immigration restric- in the labor force.It is well known that females and older tions by 0.086 on average.This estimated change has a people have much lower labor-force participation rates than standard error of 0.031 and a 90%-confidence interval of the overall population (-0.138,-0.036).The 1992 results for Education Years are If Occupation Wage and Education Years measure labor- similar:increasing Education Years from its mean to its market skills,then the correlation between these regressors maximum (approximately 12.9 years to 17 years),holding and Immigration Opinion should hold among only labor- fixed all other regressors at their means,reduces the prob- force participants.If these regressors measure non-labor- ability of supporting immigration restrictions by 0.126 on market considerations,then their explanatory power should average.This estimated change has a standard error of 0.029 not vary across the two subsamples.Table 4 reports the and a 90%-confidence interval of (-0.174,-0.081).All results.For the labor force subsample,both Occupation three years give the same result:higher skills are strongly Wage and Education Years are strongly significant,with larger coefficient estimates than the full-sample estimates and significantly correlated with lower probabilities of sup- from table 2.For the not-in-labor-force subsample,the coefficient estimates are much smaller than the full-sample 15 For our simulation procedures,we used the Stata program CLARIFY significance of the effects of several control variables differs across the (Tomz,Wittenberg,&King,1998).These procedures are discussed in two methodologies. King et al.(2000). This content downloaded from 202.120.14.193 on Mon,15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

LABOR MARKET COMPETITION AND INDIVIDUAL PREFERENCES OVER IMMIGRATION POLICY 141 The actual coefficient estimates in table 2 identify the qualitative effect on Immigration Opinion of skills and our other regressors. However, these coefficients do not answer our key substantive question of how changes in skill levels affect the probability that an individual supports immigration restrictions. To answer this question, we used the estimates of model 1 and 2 to conduct simulations that calculate the effect on immigration preferences of changing skills, while holding the other variables constant at their sample means. Our simulation procedure works as follows. Recognizing that the parameters are estimated with uncertainty, we drew 1,000 simulated sets of parameters from their sampling distribution defined as a multivariate normal distribution with mean equal to the maximum-likelihood parameter estimates and variance equal to the variance-covariance matrix of these estimates. For each of the 1,000 simulated sets of coefficients, we then calculated two probabilities. Setting all variables equal to their sample means, we first calculated the estimated probability of supporting immigration restrictions (that is, the probability of supporting a reduction in immigration by either "a lot" or "a little"). We then calculated the estimated probability of supporting immigration restrictions when our skills measure is increased to its sample maximum, while holding fixed all other regressors at their means. The difference between these two estimated probabilities is the estimated difference in the probability of supporting immigration restrictions between an individual with average skills and someone with "maximum" skills. We calculated this difference 1,000 times, and then-to show the distribution of this difference-we calculated its mean, its standard error, and a 90%-confidence interval around the mean. Table 3 reports the results of this simulation for our two skills regressors. For 1992, increasing Occupation Wage from its mean to its maximum ($512 per week to $1138 per week), holding fixed all other regressors at their means, reduces the probability of supporting immigration restrictions by 0.086 on average. This estimated change has a standard error of 0.031 and a 90%-confidence interval of (-0.138, -0.036). The 1992 results for Education Years are similar: increasing Education Years from its mean to its maximum (approximately 12.9 years to 17 years), holding fixed all other regressors at their means, reduces the probability of supporting immigration restrictions by 0.126 on average. This estimated change has a standard error of 0.029 and a 90%-confidence interval of (-0.174, -0.081). All three years give the same result: higher skills are strongly and significantly correlated with lower probabilities of supporting immigration restrictions. (Table A2 gives simulation results for all variables in model 1 and 2).15 One possible objection to our analysis is the claim that Occupation Wage and Education Years measure labor-market skills. For example, Education Years might indicate greater tolerance or civic awareness. To test this possibility, we split our sample between those in the labor force and those not in the labor force and then reestimated model 1 and 2 on each subsample. We defined the subset of laborforce participants as those individuals reporting that they were either employed or unemployed but seeking work. In every year, the not-in-labor-force subsample was disproportionately female: approximately two females for every male, versus a majority of males in the labor-force group. In every year, the not-in-labor-force subsample was also much older: an average age of approximately sixty versus forty for those in the labor force. It is well known that females and older people have much lower labor-force participation rates than the overall population. If Occupation Wage and Education Years measure labormarket skills, then the correlation between these regressors and Immigration Opinion should hold among only laborforce participants. If these regressors measure non-labormarket considerations, then their explanatory power should not vary across the two subsamples. Table 4 reports the results. For the labor force subsample, both Occupation Wage and Education Years are strongly significant, with larger coefficient estimates than the full-sample estimates from table 2. For the not-in-labor-force subsample, the coefficient estimates are much smaller than the full-sample TABLE 3.-ESTIMATED EFFECT OF INCREASING SKILL LEVELS ON THE PROBABILITY OF SUPPORTING IMMIGRATION RESTRICTIONS Increase Skill Measure Change in Probability of From Mean to Supporting Immigration Maximum Year Restrictions Occupation Wage 1992 -0.086 (0.031) [-0.138, -0.036] Education Years -0.126 (0.029) [-0.174, -0.081] Occupation Wage 1994 -0.337 (0.050) [-0.416, -0.252] Education Years -0.112 (0.019) [-0.143, -0.0811 Occupation Wage 1996 -0.201 (0.047) [-0.274, -0.120] Education Years -0.085 (0.017) [-0.113, -0.057] Using the estimates from model I and 2, we simulated the consequences of changing each skill measure from its mean to its maximum on the probability of supporting immigration restrictions. The mean effect is reported first, with the standard error of this estimate in parentheses followed by a 90%-confidence interval. significance of the effects of several control variables differs across the two methodologies. 15 For our simulation procedures, we used the Stata program CLARIFY (Tomz, Wittenberg, & Kirng, 1998). These procedures are discussed in King et al. (2000). This content downloaded from 202.120.14.193 on Mon, 15 Feb 2016 10:04:26 UTC All use subject to JSTOR Terms and Conditions

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