Evidence from Firm-level Data in Vietnam

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this analysis, especially the estimation of TFP. In setting the region dummies, we use the classification ofregions used in the survey. In this survey, there are five regions into which firms are classified: Red RiverDelta, Southern Central Costal, South East, Mekong River Delta and Northern Central. All these dummies arealso summarized in Table 2.V. RESULTS AND DISCUSSIONTable 3 describes differences between exporters and non-exporters in a range of characteristics. The firstcolumn lists the characteristics in which the differences are examined. The second and fourth columns reportthe simple exporter premium and the conditional exporter premium, respectively. The simple exporterpremium is the percentage difference between exporters and non-exporters in the mean level of thecharacteristic in consideration, without controlling for differences in other characteristics, industry or locationof firms. The conditional exporter premium is also the difference in the mean level but is calculated with othercharacteristics, location and industry type of firms being controlled for. The third and fifth columns list thecorresponding standard errors and t-statistics of these differences. At the unconditional mean, revenue andemployment levels in exporting firms are about 300 per cent greater than those in non-exporters. Exporters’capital scale is also larger, around 230 per cent. The positive premium of exporters in the conditional meanlevels of these characteristics remain the same, although the magnitudes are smaller. All these differences arestatistically significant at 1 percent level, implying that exporters are significantly larger than non-exporters.Exporters also have high premium in total factor productivity over non-exporters, about 28.7 and 16.4 percent for the simple and the conditional, respectively. However, the table shows that exporters have lowervalue added per worker. This difference in labor productivity is not large, and even statistically insignificantfor the level in simple mean. Exporters appear to use labor-intensive technology. The ratio of capital perworker of exporters is 20 and 45 per cent lower than that of non-exporters when comparing in the simple andconditional means, respectively. Exporters appear to pay higher wage. However, this difference is notstatistically significant in both premium criteria. Related to years of experience in business, exporters areolder than non-exp orters. In summary, the data of the Vietnam PICS in 2005 hi nt that exporters inmanufacturing sector of Vietnam are “superior” to non-exporters in terms of size (employment, capital andrevenue), age and TFP. Besides, exporters appear to be involved in more labor-intensive production withlower value added per worker than their counterparts who solely serve the domestic market. There is nostatistically significant eviden ce for the difference in skills of workers employed by exporters andnon-exporters when skill is proxied by average wa ges.As argued in the previous sections, this superi ority of exporters, especially in TFP, at a givenmoment in time may be attributed to the self-sele ction into markets of superior firms or to the positive effectof learning-by-exporting process. By examining the results of the estim ation of equation (14) which we reportin Ta ble 4, we will be able to elaborate the determ inants of the former when the latter is controlled for. In sixcolumns that go after the column of variables, we report estimated coefficients that represent the marginaleffects of each explanatory variable on the value of the link function in probit models, i.e., on the value of theinverse of the standard normal cumulative distribution function (usually termed as the Z score) of theprobability to be an exporter. As it is well-known in probit models, it is complicated to interpret the marginaleffect directly on the probability of becoming an exporter. Besides, it is not much important to report thiseffect when we use the data of a sample, not the whole population, of the firms. Therefore, we choose to focus18
on the analysis of the direction of this effect, in other words, the sign of parameter estimates. This sign is alsothat of the marginal effects on the Z score that we report in Table 4.Table 3:DIFFERENCES BETWEEN EXPORTERS AND NON-EXPORTERSSimpleConditionalStandard errorsVariables ExporterExporterStandard errorsPremium (%)Premium (%)Revenue 285.38 0.0669 *** 51.55 0.0384 ***TFP 28.66 0.0613 *** 16.39 0.0408 ***Labor Productivity -1.91 0.0418 -11.52 0.036 ***Employment 313.80 0.0496 *** 158.56 0.0521 ***Average Wage 3.29 0.0281 4.50 0.0283Capital 227.52 0.0736 *** 150.58 0.0726 ***Capital Intensity -20.05 0.0556 *** -44.68 0.0405 ***Age 33.17 0.0466 *** 14.57 0.0527 **Note:*** , ** , and * indicate significance at 1%, 5%, and 10% levels, respectively.The first three columns of Table 4 list the estimated parameters in estimations that include thenatural logarithm of TFP in the vector of explanatory variables, and the last three present the results ofregressions that use the natural logarithm of labor productivity in the place of the logarithm of TFP. Themodels (1) and (4) are probit in pooled data; (2) and (5) the Heckman’s random-effects dynamic probit; and(3) and (6) the random-effects probit in the sample of non-status-switchers. We do not list the parameterestimates of industry and region dummies in Table 4 and refer readers to the full results in Table A.2 in theAppendix.We are now first to interpret the estimation results described in Table 4, and then to raise somecomments on important points of these results. It shows in Table 4 that the most important determinant is theexporting experience. Exporting last year is a good predictor of exporting this year. Being an exporter in theprevious period raises the Z score by more than 320 per cent in the poole d probit specifications. As explainedin the empirical background, this level is the upper bound of the parameter estimate due to the upward bias ofthe estimations using pooled data without co ntrolling for unobserved firm effects. Howev er, the positiverelation is still seen in our preferred estimation in Heckman’s random-effects dynamic probit specifications.The marginal effect on the Z score remains high at about 200 per cent, two thirds of the upper bound. Thisimportant effect of past behavior in exporting is usuall y interpreted as the evide nce of sunk en try costs, ashinted in the theoretical background.However, there is no statistically significant evidence that firms in Vietnam with higher TFP levelself-select into serving foreign mar kets. In the regression using the p ooled data se t, the effect o f the logarithmof TFP last year on the Z score th is year is negative at the significance level of 10 per cent. Th is implies thereis a negative relationship between TFP level in the previous year and the likelihood to be an exporter this year.This effect becomes statistically insignificant, tho ugh still negative, in the dynamic random-effectsspecification whose results are rep orted in column (2). When we exclude the laggeddependent variable from19
Page 1 and 2: ENTRY COSTS AND HETEROGENEOUS CHARA
Page 3 and 4: certainly different among firms. Th
Page 5 and 6: towards more productive firms. Firm
Page 7 and 8: In the framework of multiple period
Page 9 and 10: expenses and assets.Table 1: SAMPLE
Page 11 and 12: variable when there is the phenomen
Page 13 and 14: are vectors of parameters; andvitis
Page 15 and 16: that determines export status and p
Page 17: combine Rubbe r and Plastic Product
Page 21 and 22: Besides TFP, we also use labor prod
Page 23 and 24: an important factor that guides fir
Page 25 and 26: APPENDIX(1) Estimation of total fac
Page 27 and 28: Table A.1:COEFFICIENTS OF PRODUCTIO
Page 29 and 30: (0.3254) (0.4484) (0.6159) (0.3229)
Page 31 and 32: Falvey, R., D. Greenaway and Z. Yu,

Evidence from Firm-level Data in Vietnam

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