1. Government Trust and Macro economic Variables - Focusing Approval Rating of President MB Lee Yoonseuk Woo Soongsil University

2.  There are loads of literature regarding government trust.  Most studies are related to the relationship between personal perception of government such as satisfaction about government policy or leadership, and variables of personal orientation such as political attitude, experience of participation, understading about policy outcomes, socioeconomic status and so forth.  Methodologically, most of them are cross-sectional and micro-level analysis. Background of the Research

3. Blind (2006: 8)

4. Bouckaert & Walle (2003: 335)

5.  Most of the Korean literature tried to find out dominant factors among different individual experience or status influencing individual perception about government, policy or leadership.  However, longitudinal change of aggregate support for president is more of interest than individual perception toward government or policy at certain cross-sectional time, since it shows change of overall level of support from public as a kind of input rather than simplistic personal response to government according to their private experience or emotion. It is particularly true for countries like Korea where imperial presidency has super power in every part of policy issues.  It is necessary to test whether aggregate support change is influenced by change of macro economic variables or not to find empirical evidence of relationship between them. Background of the Research

6.  Incumbent president of Korea, MB Lee, was a CEO of famous conglomerate and was believed to bring economic prosperity to Korea.  Different from his predecessor who was immersed in ideological issues, public support to MB seems to be more related with macro economic indices.  However, although Korea is said to successfully overcome worldwide economic crisis among other countries, popularity of this government is relatively low. Korean situation

7.  The purpose of this study is to find out whether change of public support for president is related to macro economic variables or not, and if then, which variables have significant impact on it.  Approval rating changes of President Lee (% of respondents who answered he is performing government affairs well, weekly surveyed by Realmeter for 1,000 people) is used as a surrogate variable of government trust. We assume that it represents both political and social trusts.  For this purpose, we are going to analyze the relationship between time-series variables of macro economic factors representing economy, export, production and consumption (from Financial Statistics Information System), and approval rating of MB. Research Question and Methods

8. Approval rating (%) changes of MB (3/2008~1/2012)

13. Correlation Unemployment, Export and Bank loan overdue are related with Approval rate; however, sign of unemployment (+) is against expectation. As there should be time lag, simple correlation of cross sectional time may not significant.

14. Regression R 2 of regression is quite low, and there seems to be autocorrelation problem since they are time-series data, which undermines significance of regression analysis. Unemployment, Export and Production capacity are significant; but sign of unemployment and production capacity are against expectation.

15. If then X → Y Y → X No relationship X → Y, Y → X thus Granger causality test needed

16.  Seasonal adjustment was applied to all the variables by X- 12 method using E-Views program.  Augmented Dickey Fuller unit root test was applied to all the variables.  From the result, Amount of orders of construction, Current account, and Unemployment do not have unit roots and thus were used without differentiation. The others have unit roots, and thus Approval rate, CPI, Export, Bank loan overdue are first differentiated; KOSPI and Production capacity are second differentiated. Unit Root Test for time-series data

17. Granger causality with KOSPI Null Hypothesis:Lags Obs F- StatisticProb. D2_KOSPI_SA does not Granger Cause D1_APPRATE_SA D1_APPRATE_SA does not Granger Cause D2_KOSPI_SA 243 1.00938 0.01811 0.3740 0.9821 342 0.63510 0.25574 0.5974 0.8567 441 0.33641 0.84516 0.8514 0.5071 540 0.81057 0.64097 0.5517 0.6703 KOSPI has no Granger causality with Approval rate.

18. Granger causality with unemployment Null Hypothesis:Lags Obs F- StatisticProb. D1_APPRATE_SA does not Granger Cause UNEMP_SA UNEMP_SA does not Granger Cause D1_APPRATE_SA 244 0.83562 0.78741 0.4412 0.4621 343 0.43115 1.52253 0.7320 0.2252 442 1.09687 3.27611 0.3744 0.0228 541 0.55910 4.42554 0.7303 0.0039 Unemployment has Granger causality with Approval rate in 4 and 5 lags.

19. Granger causality with Export Null Hypothesis:Lags Obs F- StatisticProb. D1_EXPORT_SA does not Granger Cause D1_APPRATE_SA D1_APPRATE_SA does not Granger Cause D1_EXPORT_SA 244 0.36821 3.06854 0.6944 0.0579 343 0.34202 1.71502 0.7951 0.1812 442 0.25487 1.03058 0.9046 0.4061 541 0.21564 1.95924 0.9531 0.1138 Export has no Granger causality with Approval rate. Approval rate has Granger causality with Export in 2 lags, but non-sense.

20. Granger causality with Current Account Null Hypothesis:Lags Obs F- StatisticProb. CURACC_SA does not Granger Cause D1_APPRATE_SA D1_APPRATE_SA does not Granger Cause CURACC_SA 244 0.84231 1.65303 0.4384 0.2046 343 0.30838 2.41287 0.8192 0.0826 442 0.33703 0.58677 0.8510 0.6745 541 0.34843 0.32536 0.8792 0.8937 Current Account has no Granger causality with Approval rate.

21. Granger causality with Production capacity Null Hypothesis:Lags Obs F- StatisticProb. D2_PRODCAP_SA does not Granger Cause D1_APPRATE_SA D1_APPRATE_SA does not Granger Cause D2_PRODCAP_SA 243 0.12848 0.44719 0.8798 0.6427 342 2.09640 1.27360 0.1184 0.2985 441 3.15628 1.45315 0.0270 0.2395 540 2.29846 1.17488 0.0709 0.3454 Production capacity of manufacturing industry has Granger causality with Approval rate in 4 lags.

22. Granger causality with Orders of construction Null Hypothesis:Lags Obs F- StatisticProb. CONORD_SA does not Granger Cause D1_APPRATE_SA D1_APPRATE_SA does not Granger Cause CONORD_SA 244 0.14402 2.69808 0.8663 0.0799 343 0.91869 1.40729 0.4416 0.2565 442 1.10370 2.22453 0.3712 0.0877 541 0.88055 2.58621 0.5061 0.0464 Value of construction order has no Granger causality with Approval rate. Approval rate has Granger causality with ConOrd in 5 lags, but non-sense.

23. Granger causality with CPI Null Hypothesis:Lags Obs F- StatisticProb. D1_CPI_SA does not Granger Cause D1_APPRATE_SA D1_APPRATE_SA does not Granger Cause D1_CPI_SA 244 0.06051 0.37072 0.9414 0.6926 343 2.21657 0.27550 0.1030 0.8427 442 1.78594 0.34673 0.1552 0.8444 541 1.24306 0.43672 0.3140 0.8193 CPI has no Granger causality with Approval rate.

24. Granger causality with Bank loan overdue Null Hypothesis:Lags Obs F- StatisticProb. D1_LOANOVER_SA does not Granger Cause D1_APPRATE_SA D1_APPRATE_SA does not Granger Cause D1_LOANOVER_SA 244 1.05945 0.25276 0.3564 0.7779 343 0.53754 0.36170 0.6596 0.7810 442 0.41227 0.08999 0.7985 0.9850 541 0.70556 0.08830 0.6238 0.9935 Bank loan over has no Granger causality with Approval rate.

25. Granger causality summaries VariablesGranger Causality KOSPINone UnemploymentUnemployment → AR, 4&5 lags ExportAR → Export, 2 lags Current AccountNone Production CapacityPC → AR, 4 lags Construction OrderAR → CO, 5 lags CPINone Loan overNone

26. Impulse response analysis When Unemployment increases, App. rate increases till 2 months, then decreases till 3 months, and slightly increases before it disappears. When Production capacity increases, App. rate decreases till 2 months, then fluctuate till 6 months before it disappears. = Bizarre conclusion : bad economy leads to higher App. rate and good production leads to lower App. rate ?

27.  Most of macro economic time-series variables representing economy, export, production and consumption do not have Granger causality with approval rate of president Lee. Although unemployment and production capacity have Granger causality with approval rate, their impact on approval rate was against our expectation.  From the result, we conclude; As Lawrence(1998)* acknowledged, due to reduced role of government in national economy, level of approval rate of president as government trust does not seem to go together with economic ups and downs. More empirical evidences are needed to identify whether there are other significant macro economic variables or not. Also, meaning of this result is to be further analyzed: does gov’t still needs to consider level of gov’t trust or not in economic policy?; gov’t trust is a valuable index to evaluate gov’t performance or not? Implication and Discussion * “Is it Really the Economy Stupid?” in Joseph Nye, Philip D. Zelikow and David C. King, editors, Why People Don’t Trust Government (Cambridge, Mass: Harvard University Press) 1997