Katerina Tertytchnaya et al. TABLE 4.A Reduction in Remittances on originating from elsewhere.While this behavior is ra- Government Approval and Economic Blame tional,particularly in a context where economic per- formance is largely driven by exogenous shocks,it has Attribution implications for the economic vote as an instrument of Economic accountability (e.g.Campello and Zucco 2017). Government Blame There may be another mechanism at work here how- Approval Attribution ever,where households update their evaluations of in- Model(1) Model(2) cumbent competence,because they think the incum- bent facilitates,or hinders remittance transfers.If that Reduction in Remittances -0.038* 0.079* were the case,we would expect that fluctuations in re- (0.018) (0.043) mittances should exclusively influence support for the Age 0.001** -0.003** president,or central government authorities.Yet,as we (0.0005) (0.001) show in Table D.2 in the SI,fluctuations in remittances Gender -0.069** -0.043 (0.014) also influence support for local community leaders.Ar- (0.032) Married -0.008 0.095* guably,it is unlikely that local community leaders could (0.014) (0.033) manipulate remittance inflows,or that voters would ex- Employed 0.027* -0.026 pect them to,as they lack the authority to manipulate (0.015) (0.035) the official exchange rate or to introduce schemes to Wealth Index -0.004 -0.073* encourage migrants to remit more. (0.004 (0.010) In a similar vein,one could argue that households Education -0.011 -0.048* affected by a decline in remittances are holding incum- (0.012) (0.027) bents accountable for either failing to prevent declines Life Satisfaction 0.165* -0.141* in remittances,and/or for failing to 'treat'the welfare (0.007 (0.015) Risk Attitude consequences of the decline.As Ashworth,Bueno de -0.001 -0.003 (0.003) (0.007) Mesquita,and Friedenberg (2018)have argued,even Annual Growth 0.101* -0.122* exogenous shocks provide an opportunity for voters (0.021) (0.041) to learn new information about an incumbent.Here Constant 2.008** 0.798** the change in remittances would be such a shock,and (0.096) (0.197) the ability of the government to respond to this shock Likelihood -22444 -12323 or their preparedness to compensate its consequences AIC 44914.45 24670.72 could give voters new information about the incum- BIC 45015.38 24765.37 bent (e.g.Acevedo 2016).As such,voters who expe- Individuals 17,389 19,684 rience a decline in remittances may disapprove of the Countries 28 28 incumbent not because of a mechanism underpinned by misattribution,but one rooted in an increased need 9 Notes:Table entries are HLM regression coefficients with stan- dard errors in parentheses for model 1 and HLM logistic re- for national public services.If this were the case.vot- gression coefficients with standard errors in parentheses for ers could be punishing governments for their response model 2.In both models individuals are nested in countries. to the exogenous shock,rather than for the decline in For robustness checks see Table C.15 in the Sl.Significant at P00501g the**p≤0.01，tp≤0.05，*p≤0.10 level..Source:Life in remittances.This is what we call the treatment respon- Transition Survey,2010. sibility mechanism (Javeline 2003). Can we separate out these different mechanisms from our results?Although given the observational na- ture of our data we cannot be definitive.based on three countries with higher growth,while blame attribution points that we discuss below,we believe that the weight is lower.Overall,the evidence presented in Table 4 of evidence is more strongly in line with the misattri- corroborates our results from the Kyrgyz sample. bution mechanism.To begin with,in our analysis of People who experience a reduction in remitted income changes in incumbent approval,we relied on a contin- are less likely to be satisfied with the government's uous measure of changes in remittances (see Table 2). record and more likely to blame the government for a The evidence suggested that while decreases in remit- deterioration of economic conditions.Altogether,the evidence suggests remittances can drive fluctuations in tances coincided with a decline in trust in the presi- dent,increases in remittances led to an increase in trust incumbent approval in recipient countries. in the president.While it would make sense that re- cipients would punish governments for a lack of pre- EVALUATING THE MECHANISM paredness when remittances decline,rewarding gov- ernments when remittances increase is probably not In the previous sections,we have theoretically argued suggestive of this mechanism.It is not clear what re- and empirically demonstrated that changes in remit- cipients would be rewarding the government for post tances drive fluctuations in economic assessments and facto,or how this would translate into new informa- evaluations of the incumbent.We have also suggested tion.Unlike the situation with a sharp decline in re- that this relationship can be understood as a form of mittances,which could be considered an exogenous misattribution.in the sense that voters are rewarding shock,and recipients can infer new information from or punishing incumbents for economic developments the degree of government preparedness because they 770Katerina Tertytchnaya et al. TABLE 4. A Reduction in Remittances on Government Approval and Economic Blame Attribution Economic Government Blame Approval Attribution Model (1) Model (2) Reduction in Remittances − 0.038∗∗ 0.079∗ (0.018) (0.043) Age 0.001∗∗∗ − 0.003∗∗∗ (0.0005) (0.001) Gender − 0.069∗∗∗ − 0.043 (0.014) (0.032) Married − 0.008 0.095∗∗∗ (0.014) (0.033) Employed 0.027∗ − 0.026 (0.015) (0.035) Wealth Index − 0.004 − 0.073∗∗∗ (0.004) (0.010) Education − 0.011 − 0.048∗ (0.012) (0.027) Life Satisfaction 0.165∗∗∗ − 0.141∗∗∗ (0.007) (0.015) Risk Attitude − 0.001 − 0.003 (0.003) (0.007) Annual Growth 0.101∗∗∗ − 0.122∗∗∗ (0.021) (0.041) Constant 2.008∗∗∗ 0.798∗∗∗ (0.096) (0.197) Log Likelihood −22444 −12323 AIC 44914.45 24670.72 BIC 45015.38 24765.37 Individuals 17,389 19,684 Countries 28 28 Notes: Table entries are HLM regression coefficients with stan￾dard errors in parentheses for model 1 and HLM logistic re￾gression coefficients with standard errors in parentheses for model 2. In both models individuals are nested in countries. For robustness checks see Table C.15 in the SI. Significant at the ∗∗∗ p ≤ 0.01, ∗∗ p ≤ 0.05, ∗ p ≤ 0.10 level. Source: Life in Transition Survey, 2010. countries with higher growth, while blame attribution is lower. Overall, the evidence presented in Table 4 corroborates our results from the Kyrgyz sample. People who experience a reduction in remitted income are less likely to be satisfied with the government’s record and more likely to blame the government for a deterioration of economic conditions. Altogether, the evidence suggests remittances can drive fluctuations in incumbent approval in recipient countries. EVALUATING THE MECHANISM In the previous sections, we have theoretically argued and empirically demonstrated that changes in remit￾tances drive fluctuations in economic assessments and evaluations of the incumbent. We have also suggested that this relationship can be understood as a form of misattribution, in the sense that voters are rewarding or punishing incumbents for economic developments originating from elsewhere. While this behavior is ra￾tional, particularly in a context where economic per￾formance is largely driven by exogenous shocks, it has implications for the economic vote as an instrument of accountability (e.g. Campello and Zucco 2017). There may be another mechanism at work here how￾ever, where households update their evaluations of in￾cumbent competence, because they think the incum￾bent facilitates, or hinders remittance transfers. If that were the case, we would expect that fluctuations in re￾mittances should exclusively influence support for the president, or central government authorities. Yet, as we show in Table D.2 in the SI, fluctuations in remittances also influence support for local community leaders. Ar￾guably,it is unlikely that local community leaders could manipulate remittance inflows, or that voters would ex￾pect them to, as they lack the authority to manipulate the official exchange rate or to introduce schemes to encourage migrants to remit more. In a similar vein, one could argue that households affected by a decline in remittances are holding incum￾bents accountable for either failing to prevent declines in remittances, and/or for failing to ‘treat’ the welfare consequences of the decline. As Ashworth, Bueno de Mesquita, and Friedenberg (2018) have argued, even exogenous shocks provide an opportunity for voters to learn new information about an incumbent. Here the change in remittances would be such a shock, and the ability of the government to respond to this shock or their preparedness to compensate its consequences could give voters new information about the incum￾bent (e.g. Acevedo 2016). As such, voters who expe￾rience a decline in remittances may disapprove of the incumbent not because of a mechanism underpinned by misattribution, but one rooted in an increased need for national public services. If this were the case, vot￾ers could be punishing governments for their response to the exogenous shock, rather than for the decline in remittances. This is what we call the treatment respon￾sibility mechanism (Javeline 2003). Can we separate out these different mechanisms from our results? Although given the observational na￾ture of our data we cannot be definitive, based on three points that we discuss below, we believe that the weight of evidence is more strongly in line with the misattri￾bution mechanism. To begin with, in our analysis of changes in incumbent approval, we relied on a contin￾uous measure of changes in remittances (see Table 2). The evidence suggested that while decreases in remit￾tances coincided with a decline in trust in the presi￾dent, increases in remittances led to an increase in trust in the president. While it would make sense that re￾cipients would punish governments for a lack of pre￾paredness when remittances decline, rewarding gov￾ernments when remittances increase is probably not suggestive of this mechanism. It is not clear what re￾cipients would be rewarding the government for post facto, or how this would translate into new informa￾tion. Unlike the situation with a sharp decline in re￾mittances, which could be considered an exogenous shock, and recipients can infer new information from the degree of government preparedness because they 770 Downloaded from https://www.cambridge.org/core. Shanghai JiaoTong University, on 26 Oct 2018 at 03:53:04, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055418000485