194 the differences for the period 1985-1995. As an alternative to using the begin-of-period value for the factor shares (e.g. Leamer 1996 a), the average factor shares over the period have been considered (Feenstra and Hanson 1999 and Haskel and Slaughter 2001). For total factor productivity the original data, using a standardized labour share of 70 per cent, as well as estimates using actual labour shares have been considered.
Though the results appear to be rather sensitive to alternative specifications, the conclusion that there is little evidence to support substantial Stolper-Samuelson effects for EU countries, in the period considered, is consistently confirmed. The indication of technological change induced by trade with Asian Tigers, as found in table 4.12, is not always supported by other estimations, even at the 10 per cent error level.
4.4 Mandated Wage Estimation with Foreign Outsourcing
Although the mandated wage procedure is developed as a tool to estimate Stolper-Samuelson effects (i.e. the impact of changes in import prices on wage inequality through changes in domestic prices), Feenstra and Hanson (1999) did not consider import prices but variables reflecting foreign outsourcing as determinants of domestic price changes and TFP.
In the model proposed by Feenstra and Hanson (see section 3.1.2), foreign outsourcing will actually increase the domestic prices of intermediate inputs as these will become more skill-intensive, after the production of less skill-intensive inputs have been outsourced to low-skill abundant countries. They defined a modified Stolper-Samuelson theorem linking relative prices of intermediate inputs to relative wages. In their empirical work they considered volumes of imported intermediate inputs, derived from input-output tables. They defined foreign outsourcing as (Feenstra and Hanson 1999: p. 924):
inputpurchasesofgood jbyindustryi.consumptioimportsofnofgoodgoodj jj
(4.7)
If all non-energy intermediate inputs (i.e. inputs from all manufacturing industries j) are considered, (4.7) gives a broad measure of foreign outsourcing whereas if only those intermediate inputs from the same two-digit industry are considered Feenstra and Hanson defined the measure as foreign outsourcing in the narrow sense.
195 As pointed out in section 3.1.2, whereas Feenstra and Hanson concluded that foreign outsourcing harms low-skilled workers, other theoretical models have more ambiguous conclusions as to the impact on the position of low-skilled workers.
To estimate the impact of foreign outsourcing on wage inequality in the European Union the dataset used for the previous mandated wage regressions was extended with data from the OECD Input-Output database. At present the OECD data cover the period 1973-1990 but the OECD is in the process of updating the database. The database contains separate matrices of flows of imported intermediate inputs. For Belgium the input-output data of the Federal Planning Bureau were used. Bilateral import shares were considered to decompose flows of imported intermediate inputs into flows imported from six country groups: Central- and Eastern European emerging economies, (South-) East Asian Newly Industrialised Countries, Latin-American Newly Industrialised Countries, low-wage EU countries, high-wage EU countries and non-EU OECD countries (see section 4.2 for a detailed list of the countries considered).
There were sufficient data to construct all necessary variables for Belgium, Denmark, France, Germany and the United Kingdom for the period 1985-1995. The flow matrices of imported intermediate inputs of 1990 are used as no more recent data were available.
Table 4.14 shows the results of the first step price regression, with foreign outsourcing variables as determinants.
The first column reports the results of a specification in which plain TFP is used and which considers foreign outsourcing in the narrow sense (i.e. intra-sector).
For an estimation at the two-digit sector level this measure of outsourcing seems more appropriate than using the broader definition. In the second column effective TFP is used instead of plain TFP and in the final column a specification with plain TFP and variables reflecting foreign outsourcing in the broad sense.
None of the outsourcing variables appears to have had a significant impact on domestic prices in the period considered. The TFP pass-through is again highly significant and very close to the estimate reported in table 4.4.
196 Table 4.14: First Step Price Regression- Foreign Outsourcing (1985-1995)
Note: The dependent variable is the change in domestic value added prices. All variables are changes over the period 1985-1995, except for France for which changes over the period 1990-1996 have been rescaled (omitting France gives similar results).
In table 4.15 the results of the first step TFP regression, with outsourcing variables in the narrow sense, are reported.
As in the first step price regression with import prices as determinants, international R&D spillovers are found to be significant as is the negative sign of the (South-) East Asian NIC trade variable. However, where the negative sign in table 4.8 is supportive of trade-induced technological change (i.e. decreasing import prices increase TFP) a negative sign in a specification with outsourcing variables as determinants does not seem to support the model by Feenstra and Hanson (1996) as in this model it is assumed that low-skill activities will be transferred abroad, thus lifting the domestic skill level. Foreign outsourcing with (South-) East Asian NIC actually would have decreased TFP.
The second step mandated wage regressions with foreign outsourcing variables do not result in any significant coefficient.
Dependent variable: Δln pVA Narrow (TFP) Narrow (ETFP) Broad (TFP) Independent variables:
197 Table 4.15: First Step TFP Regression- Foreign Outsourcing (1985-1996)
Note: The table reports results of a fixed effects estimations with foreign outsourcing in the narrow sense as determinant. White heteroskedastic-consistent t-values in brackets. ***- **-* denotes significance at respectively 1%-5% and 10% level.
Dependent variable: TFP
Independent variables:
Domestic R&D stock (intra-sector) 0.08 (0.86) Domestic R&D stock (inter-sector) -0.08 (-0.58)
Foreign R&D stock 0.25 (2.42) **
High-wage EU Countries -0.55 (-0.23)
Low-wage EU countries 10.58 (-1.57)
non-EU OECD -5.25 (-1.25)
(South-) East Asia -0.35 (-3.44) ***
Central and Eastern Europe -0.22 (-0.71)
Latin America -0.18 (-0.30)
R2adjusted 0.11
F-test: common intercept and slopes versus country-specific
intercepts and slopes. (p-values in brackets) 1.91 (0.10) * F-test: common slopes versus country-specific slopes, given
country specific intercept. (p-values in brackets) 1.75 (0.14) F-test: common intercept versus country-specific intercepts,
given common slopes. (p-values in brackets) 2.09 (0.10)*
198 4.5 Conclusions
The two-step mandated wage regression procedure, proposed by Feenstra and Hanson (1999) and Haskel and Slaughter (2001), is a convenient tool to disentangle the impact of international trade on wage inequality from the impact of technological change, accounting for the potential indirect impact of international trade, i.e. technological change induced by international trade or trade-related R&D spillovers. The procedure sets off with the zero profit condition of perfect competition to derive a relationship between changes in domestic product prices, total factor productivity (TFP) and changes in factor rewards.
In a first step estimation, the changes in product prices and TFP are regressed on a number of potential determinants like import prices.
In a second step the estimated contributions of the exogenous determinants are regressed on factor shares. The estimated coefficients in the second step provide an estimate of the changes in factor rewards that were mandated by the changes in domestic product prices, caused by the respective determinants.
The procedure is closely linked to the Stolper-Samuelson theorem, which states that changes in import prices will, through their impact on domestic product prices, cause changes in factor rewards.
Two-step mandated wage estimations for a panel of nine EU countries, in the period 1985-1998, provide little support for Stolper-Samuelson effects of international trade with Newly Industrialised Countries (NIC). If there is some evidence that import competition of low-wage EU countries affected domestic product prices in the period 1985-1995 this effect does not seem to have carried over in factor price changes. Import competition of the Asian Tigers increased the relative wages of high-skilled workers in the European Union, as expected, but this effect is only significant at the 10 per cent error level and it is moreover not consistently confirmed in alternative specifications.
The impact of technological change on factor prices, through R&D activities, is rather country-specific and the panel estimations do not provide evidence of skill-biased technological change having caused a common drop in the relative wages of low-skilled workers.
International trade-related knowledge spillovers are, in line with previous studies, consistently found to be significant. In addition, import price competition of the Asian Tigers appears to have caused technological change which decreased the relative wages of high-skilled workers,
199 i.e. seems to point at technological change biased in favour of low-skilled workers though the latter result is not very robust.
As foreign R&D activities appear to affect technological change to a larger extent than domestic R&D activities, which undoubtedly have an important role in reinforcing a country's technological absorptive capacity, the indirect impact of international trade may be quite substantial and clearly needs to be accounted for.
The evidence of trade-related North-South spillovers (e.g. Coe, Helpman and Hoffmaister 1995) moreover shows that international trade may help Southern countries to raise their technological level, thereby inducing Northern countries to invest in R&D activities to maintain their technological lead.
International trade and technological change are clearly intertwined and the exclusive focus on either one to explain changes in the labour market does not seem warranted.
The lack of evidence of the impact of import price changes of Newly Industrialised Countries in the European Union is probably not that surprising given the mixed evidence of changes in wage inequality and the institutional differences between EU countries. It does however not imply that international trade did not have any labour market impact. The assumption of perfect labour markets, which contrary to most other assumptions of the Heckscher-Ohlin model is essential for the Stolper-Samuelson theorem to hold, is probably too heroic.
In the next two chapters this assumption is relaxed, allowing for unemployment to arise due to a fall in labour demand, if wages are sticky.