PDF, GB, 139 p., 796 Ko - Femise
PDF, GB, 139 p., 796 Ko - Femise PDF, GB, 139 p., 796 Ko - Femise
anecdotic evidence above shows, there were cases where trade policy was changed, obviously as a result of some interest groups pressure. In the absence of direct measures of industry contributions, we have used similar variables to those used in literature, as a proxy for industry organization. These variables include: (i) Herfindahl concentration indices, (ii) capital-labour ratio (as we may expect that capital intensive industry may have more organised lobbies), (iii) export intensity (since export industries may receive special treatment by the government) and (iv) share of government subsidies in the total value of sales. The last variable requires some comments, since it has not been used in the other empirical studies. On one hand, subsidies could be treated as a variable equivalent to import duties, measuring the “remuneration” paid by the government to an industry in exchange for contributions. On the other hand, however, the receipt of subsidies by a given industry can reflect the level of political organization; organized sectors, where interest groups are stronger, can probably receive higher pecuniary benefits. In Poland, chambers of producers were not well organized, but trade unions were powerful, being able to influence governments’ decisions. That is why we treat unit subsidies as a measure which can explain the level of industry organization. We therefore construct four estimated versions of the variable I (one for each of the variables listed above) in the following way: it takes the value of 1 if the variable in question for a given industry is higher than the average for the given year and it takes the value of zero otherwise. Using the proxied variable is probably less prone to the endogeneity problem as using the contributions directly (also, Maggi and Goldberg in their sensitivity study, used non-instrumented I in the regression and obtained similar results). Thus, the full model has the following form: ti xi xi ei = γ + δI + εi 1+ t m m i i i xi = + m i ' ξ Zi μi 79 (4) , (5)
xi where ti is the tariff, ei is the elasticity of import demand, is the inverse penetration ratio, m Z i is the vector of instruments listed above, εi and μ i are error terms. In the first stage we estimate equation (5) by OLS and in the second stage include the projected inverse import penetration ratio on the right hand-side of equation (4), which we estimate by OLS. The specifications and results for both versions (model 1 and model 2) of equation (5) are given in the Table 3 of Appendix. Data on both the conventional (MFN) 48 tariffs and preferential tariffs applied towards the EU countries 49 for Poland for most of the 1990s comes from the Foreign Trade Data Center (CIHZ). These data were prepared in 8-digit Combined Nomenclature aggregation, which we aggregate into the 3-digit NACE using a Eurostat Concordance table. We use the Polish import data from Eurostat’s Comext Database as weights. The output, export, import, subsidies, capital, labour, wage data comes from Polish Central Statistical Office (GUS). Data on Herfindahl indices were calculated using the micro-level GUS data in possession of National Bank of Poland. The data on import demand elasticities were unavailable for Poland. The study often used in the literature is the Shiells, Stern and Deardorff (1986). However, since not only it provides elasticities for a different economy and period but also uses SITC 3digit classification, we have decided to set the elasticity of import demand for all sectors at -1. Our final dataset includes data for 87 NACE rev.1.1 3-digit sectors for the period of 1996- 1999. Estimation results We have estimated the system of equations (4) and (5) using two alternative versions of equation (5). The first stage results for both models are listed in the appendix. Since the variation of tariffs over time is rather low, we have decided not to use the fixed effects panel estimation. Instead we do a pooled OLS for all periods and for each period separately. The results of estimation in four different specifications (and model 1 as first stage regression) for 48 Conventional tariffs are “bound” duties applied to imports from all the WTO members. 49 Very similar tariffs were also applied to imports from EFTA and CEFTA members states. 80 i
- Page 29 and 30: Preferential trade liberalization i
- Page 31 and 32: the EU enlargement, the EFTA lost t
- Page 33 and 34: The most important of these was the
- Page 35 and 36: The Definitions of the Variables an
- Page 37 and 38: Estimates for the whole CEE sample
- Page 39 and 40: agreements is, however, mixed. Whil
- Page 41 and 42: The OLS estimates suggest that both
- Page 43 and 44: Czech Republic Estonia Hungary Lith
- Page 45 and 46: Czech Slovak Republic Estonia Hunga
- Page 47 and 48: products. The provisions of the Eur
- Page 49 and 50: foreseen to take effect in 2005. Ho
- Page 51 and 52: Similar to the AMU, the ACC was for
- Page 53 and 54: Unfortunately, the data on capital
- Page 55 and 56: Table 2. The estimates for bilatera
- Page 57 and 58: obust, while the dummy variable for
- Page 59 and 60: Yi (partner) 0.944 1.009 2.267 1.96
- Page 61 and 62: Table 4. The estimates for bilatera
- Page 63 and 64: Table 5. The estimates for bilatera
- Page 65 and 66: Agreements on the third countries a
- Page 67 and 68: Chapter 2: Grossman-Helpman Model I
- Page 69 and 70: N function (U ), given by: + ( ) u
- Page 71 and 72: ti 1+ ti xi Ii −α i mi = ⋅ ,
- Page 73 and 74: Probably the most extensive list of
- Page 75 and 76: eginning of 1990. But the tariff st
- Page 77 and 78: The non-preferential (MFN, conventi
- Page 79: have important impact on political
- Page 83 and 84: We can recover the structural param
- Page 85 and 86: Appendix Table 2 Estimation results
- Page 87 and 88: Table 4 Estimation results using mo
- Page 89 and 90: Testing Grossman-Helpman model for
- Page 91 and 92: practice most importers do not pay
- Page 93 and 94: countries were traditionally subjec
- Page 95 and 96: point to notify the US government o
- Page 97 and 98: and between 157% and 247% in 2004.
- Page 99 and 100: policy reforms. On the other hand i
- Page 101 and 102: Table 1 Estimation results for Isra
- Page 103 and 104: 1995 0.00202 [2.04]** -0.00199 [2.0
- Page 105 and 106: extended to disaggregation of burea
- Page 107 and 108: The Importance of Corruption A subs
- Page 109 and 110: transition countries. Sekkat and Ve
- Page 111 and 112: society. In addition, they show tha
- Page 113 and 114: Johnson, Kaufmann, McMillan, and Wo
- Page 115 and 116: corruption. For example, upon grant
- Page 117 and 118: and criminal prosecution. On the ot
- Page 119 and 120: estimation are likely to be influen
- Page 121 and 122: levels have been used to derive fur
- Page 123 and 124: Union. In fact, the level of regula
- Page 125 and 126: Table 2 List of the Commonly Raised
- Page 127 and 128: Table 6 Predicted improvement (show
- Page 129 and 130: SB_PR all procedures required to re
xi<br />
where ti is the tariff, ei is the elasticity of import demand, is the inverse penetration ratio,<br />
m<br />
Z i is the vector of instruments listed above, εi and μ i are error terms. In the first stage we<br />
estimate equation (5) by OLS and in the second stage include the projected inverse import<br />
penetration ratio on the right hand-side of equation (4), which we estimate by OLS. The<br />
specifications and results for both versions (model 1 and model 2) of equation (5) are given in<br />
the Table 3 of Appendix.<br />
Data on both the conventional (MFN) 48 tariffs and preferential tariffs applied towards the EU<br />
countries 49 for Poland for most of the 1990s comes from the Foreign Trade Data Center<br />
(CIHZ). These data were prepared in 8-digit Combined Nomenclature aggregation, which we<br />
aggregate into the 3-digit NACE using a Eurostat Concordance table. We use the Polish<br />
import data from Eurostat’s Comext Database as weights. The output, export, import,<br />
subsidies, capital, labour, wage data comes from Polish Central Statistical Office (GUS). Data<br />
on Herfindahl indices were calculated using the micro-level GUS data in possession of<br />
National Bank of Poland. The data on import demand elasticities were unavailable for Poland.<br />
The study often used in the literature is the Shiells, Stern and Deardorff (1986). However,<br />
since not only it provides elasticities for a different economy and period but also uses SITC 3digit<br />
classification, we have decided to set the elasticity of import demand for all sectors at -1.<br />
Our final dataset includes data for 87 NACE rev.1.1 3-digit sectors for the period of 1996-<br />
1999.<br />
Estimation results<br />
We have estimated the system of equations (4) and (5) using two alternative versions of<br />
equation (5). The first stage results for both models are listed in the appendix. Since the<br />
variation of tariffs over time is rather low, we have decided not to use the fixed effects panel<br />
estimation. Instead we do a pooled OLS for all periods and for each period separately. The<br />
results of estimation in four different specifications (and model 1 as first stage regression) for<br />
48<br />
Conventional tariffs are “bound” duties applied to imports from all the WTO members.<br />
49<br />
Very similar tariffs were also applied to imports from EFTA and CEFTA members states.<br />
80<br />
i