Trade Adjustment Costs in Developing Countries: - World Bank ...

46Erhan Artuç and John McLarenin Artuç et al. (2010). However, in that study, the data set was 26 years long; inthe present case, with only three years, that strategy is not available to us. We arehoping that after the Turkish Statistical Institute releases two more years ofhousehold survey data, we will be able to use instruments, which is left over herefor future research. As an imperfect fix, we note that in the earlier paper with USdata, estimating with OLS instead of with instruments increased the value of Cby 67 per cent and v by 54 per cent when β = 0.97, and C by 34 per cent and vby 31 per cent when β = 0.9, so we divide our parameter estimates by 1.67, 1.54,1.34 and 1.31 for an alternative set of simulations. After simulating the modelwith original estimates (for both β = 0.9 and β = 0.97), we repeat the simulationexercises with the corrected parameters, and show that the bias in the OLSestimates probably does not affect the adjustment path of workers and valuessignificantly.Table 3.4: Regression Results for Sector-specific Entry CostsBeta=0.97Beta=0.90Estimate t-statistic Estimate t-statisticv 1.60 (2.98***) 1.17 (3.95***)C 1 (Agriculture) 0.00 (0.00) 3.10 (1.53*)C 2 (Manufacture) 17.67 (2.41**) 7.17 (3.54***)C 3 (Trade) 9.90 (1.31) 5.55 (2.61***)C 4 (Service) 20.81 (5.52***) 8.65 (6.03***)T-statistics are in parentheses. One-tailed significance: 1-percent***, 5-percent**, 10-percent*.Another possible source of bias comes from the fact that we have imposeduniform moving costs for all sectors, so that. Degrees-of-freedomconcerns prevent us from estimating the full set of C ij parameters withoutrestriction, but we have also estimated the model with a slightly richerspecification allowing for sector-specific entry costs. In this approach, C ij =C j fori=1,...,4. Table 3.4 shows the results of this regression.Compared with the Basic Model regression from Table 3.3, we find that all sectorsexhibit lower entry costs. However, we were not able to identify entry cost ofAgriculture when β = 0.97, therefore we are not using results from Table 3.4 insimulations. This identification problem probably arises because of our very smallsample size. We find that entry to the Service sector (which includes governmentand professional sectors) is the most costly one, while entry to Agriculture (whichincludes only workers who do not own a farm) is the least costly.4. SIMULATION: A SUDDEN TRADE LIBERALIZATIONNow, we use the estimates to study the effect of a hypothetical trade shockthrough simulations. Note that for the estimations, the only functional formassumption we needed was the density for the idiosyncratic shocks, but tosimulate the model we need to choose functional forms (and parameter values)for production and utility functions as well. We assume that each of the four