1378 THE AMERICAN ECONOMIC REVIEW DECEMBER 2001 lowest protection against expropriation.We use useful since settler mortality is our instrument the average value for each country between for institutions (this variable is described in 1985 and 1995 (values are missing for many more detail in the next section). countries before 1985).This measure is appro- priate for our purposes since the focus here is on B.Ordinary Least-Squares Regressions differences in institutions originating from dif- ferent types of states and state policies.We Table 2 reports ordinary least-squares (OLS) expect our notion of extractive state to corre- regressions of log per capita income on the spond to a low value of this index,while the protection against expropriation variable in a tradition of rule of law and well-enforced prop- variety of samples.The linear regressions are erty rights should correspond to high values.1 for the equation The next row gives an alternative measure,con- straints on the executive in 1990,coded from (1) log yi=u aRi+X'y+8i, the Polity III data set of Ted Robert Gurr and associates (an update of Gurr,1997).Results where y is income per capita in country i,R:is using the constraints on the executive and other the protection against expropriation measure,X measures are reported in Acemoglu et al.(2000) is a vector of other covariates,and e;is a and are not repeated here. random error term.The coefficient of interest The next three rows give measures of early throughout the paper is a,the effect of institu- institutions from the same Gurr data set.The tions on income per capita. first is a measure of constraints on the executive Column (1)shows that in the whole world in 1900 and the second is an index of democ- sample there is a strong correlation between our racy in 1900.This information is not available measure of institutions and income per capita. for countries that were still colonies in 1900,so Column (2)shows that the impact of the insti- we assign these countries the lowest possible tutions variable on income per capita in our base score.In the following row,we report the mean sample is quite similar to that in the whole and standard deviation of constraints on the world,and Figure 2 shows this relationship di- executive in the first year of independence (i.e., agrammatically for our base sample consisting the first year a country enters the Gurr data set) of 64 countries.The R2 of the regression in as an alternative measure of institutions.The column (1)indicates that over 50 percent of the second-to-last row gives the fraction of the pop- variation in income per capita is associated with ulation of European descent in 1900,which is variation in this index of institutions.To get a our measure of European settlement in the col- sense of the magnitude of the effect of institu- onies,constructed from McEvedy and Jones tions on performance,let us compare two coun- (1975)and Curtin et al.(1995).The final row tries,Nigeria,which has approximately the 25th gives the logarithm of the baseline settler mor- percentile of the institutional measure in this tality estimates;the raw data are in Appendix sample,5.6,and Chile,which has approxi- Table A2. mately the 75th percentile of the institutions The remaining columns give descriptive sta- index,7.8.The estimate in column (1),0.52, tistics for groups of countries at different quar- indicates that there should be on average a 1.14- tiles of the settler mortality distribution.This is log-point difference between the log GDPs of the corresponding countries (or approximately a 2-fold difference-e14-1 2.1).In prac- i The protection against expropriation variable is spe- cifically for foreign investment,since Political and Risk tice,this GDP gap is 253 log points (approxi- Services construct these data for foreign investors.How- mately 11-fold).Therefore,if the effect ever,as noted by Knack and Keefer (1995),risk of expro- estimated in Table 2 were causal,it would im- priation of foreign and domestic investments are very highly ply a fairly large effect of institutions on per- correlated,and risk of expropriation of foreign investment formance,but still much less than the actual may be more comparable across countries.In any case,all our results hold also with a variety of other measures of income gap between Nigeria and Chile. institutions (see Tables 4a,b,c,d,and e in Acemoglu et al., Many social scientists,including Monte- 2000,available from the authors). squieu [1784](1989),Diamond (1997),and1378 THE AMERICAN ECONOMIC REVIEW DECEMBER 2001 lowest protection against expropriation. We use the average value for each country between 1985 and 1995 (values are missing for many countries before 1985). This measure is appro￾priate for our purposes since the focus here is on differences in institutions originating from dif￾ferent types of states and state policies. We expect our notion of extractive state to cone￾spond to a low value of this index, while the tradition of rule of law and well-enforced prop￾erty rights should correspond to high values." The next row gives an alternative measure, con￾straints on the executive in 1990, coded from the Polity 111 data set of Ted Robert Gun and associates (an update of Gun, 1997). Results using the constraints on the executive and other measures are reported in Acemoglu et al. (2000) and are not repeated here. The next three rows give measures of early institutions from the same Gun data set. The first is a measure of constraints on the executive in 1900 and the second is an index of democ￾racy in 1900. This information is not available for countries that were still colonies in 1900, so we assign these countries the lowest possible score. In the following row, we report the mean and standard deviation of constraints on the executive in the first year of independence (i.e., the first year a country enters the Gun data set) as an alternative measure of institutions. The second-to-last row gives the fraction of the pop￾ulation of European descent in 1900, which is our measure of European settlement in the col￾onies, constructed from McEvedy and Jones (1975) and Curtin et al. (1995). The final row gives the logarithm of the baseline settler mor￾tality estimates; the raw data are in Appendix Table A2. The remaining columns give descriptive sta￾tistics for groups of countries at different quar￾tiles of the settler mortality distribution. This is l1 The protection against expropriation variable is spe￾cifically for foreign investment, since Political and Risk Services construct these data for foreign investors. How￾ever, as noted by Knack and Keefer (1995), risk of expro￾priation of foreign and domestic investments are very highly correlated, and risk of expropriation of foreign investment may be more comparable across countries. In any case, all our results hold also with a variety of other measures of institutions (see Tables 4a, b, c, d, and e in Acemoglu et al., 2000, available from the authors). useful since settler mortality is our instrument for institutions (this variable is described in more detail in the next section). B. Ordinary Least-Squares Regressions Table 2 reports ordinary least-squares (OLS) regressions of log per capita income on the protection against expropriation variable in a variety of samples. The linear regressions are for the equation (1) log yi = p + aRi + X:y + si, where y, is income per capita in country i, R iis the protection against expropriation measure, Xi is a vector of other covariates, and si is a random enor term. The coefficient of interest throughout the paper is a, the effect of institu￾tions on income per capita. Column (1) shows that in the whole world sample there is a strong correlation between our measure of institutions and income per capita. Column (2) shows that the impact of the insti￾tutions variable on income per capita in our base sample is quite similar to that in the whole world, and Figure 2 shows this relationship di￾agrammatically for our base sample consisting of 64 countries. The R~ of the regression in column (1) indicates that over 50 percent of the variation in income per capita is associated with variation in this index of institutions. To get a sense of the magnitude of the effect of institu￾tions on performance, let us compare two coun￾tries, Nigeria, which has approximately the 25th percentile of the institutional measure in this sample, 5.6, and Chile, which has approxi￾mately the 75th percentile of the institutions index, 7.8. The estimate in column (I), 0.52, indicates that there should be on average a 1.14- log-point difference between the log GDPs of the corresponding countries (or approximately a 2-fold difference-e1.14 - 1 = 2.1). In prac￾tice, this GDP gap is 253 log points (approxi￾mately I I-fold). Therefore, if the effect estimated in Table 2 were causal, it would im￾ply a fairly large effect of institutions on per￾formance, but still much less than the actual income gap between Nigeria and Chile. Many social scientists, including Monte￾squieu [I7841 (1989), Diamond (1997), and