Imported Intermediate Inputs and Capital Goods

Transcription

1 Imported Intermediate Inputs and Capital Goods Master Thesis Name: Jeroen Meisters Thesis Supervisor: Mr. Ziesemer Student ID: i Date: 18/08/2012 School of Business and Economics

2 Table of Contents I. Introduction pp. 3-4 II. Intermediate Inputs pp Dynamic Gains pp. 6-8 Theory pp Evidence pp III. Mechanisms pp Dynamic gains from trade pp Rate of adoption pp Effect on intermediate inputs on domestic products pp Effect of tariff reductions pp IV. Policy recommendations and further discussions pp Substitutability of imports pp Labor effects pp Export competitiveness p. 46 V. Conclusion pp VI. List of abbreviations p. 49 VII. References pp

3 I. Introduction The relationship between the import of intermediate inputs, or other types of imported capital goods, and growth is at the heart of the debate in literature on productivity and growth. The debate is about how imported intermediates change the growth literature that uses neoclassical growth models. The literature has moved quite some distance from the static neoclassical model where total productivity growth (TFP) comes exogenously into the model. In this model, the dynamic effects, e.g. externalities that arise from a technology transfer to developing countries, are missed (Melo, de & Robinson (1990). Furthermore, according to Lucas (1990) there are more shortcomings to the neoclassical model. He shows these shortcomings by explaining that the neoclassical prediction of capital flows flowing from rich to poor, and thereby equalizing factor returns, and the underlying assumptions on technology and trade conditions are drastically wrong. Lucas (1990) gives possible answers to this problem. First of all, the neoclassical model does not cover differences in human capital and in relation to this; secondly, the model does not take into account the external benefits that capital transfer has on productivity. This is the same as stating that knowledge spillovers are assumed to be zero. Lastly, he mentions capital market imperfections. Colonial and imperial power played a large role in investment decisions. These shortcomings in the neoclassical literature accounted for the new paradigm of endogenous growth. This string of literature emerged in the 1980 s posit that TFP comes into the model endogenously and accounts for dynamic effects which include trade externalities. At that time countries were abandoning the import-substitution industrialization (ISI) strategy, and replacing this strategy with policies which followed an export-led growth (ELG) strategy. The ELG strategy has often been cited as the main reason to cover for differences in growth and productivity in developing countries, as this strategy involves trade externalities which are incorporated in the endogenous growth model. According to De Melo and Robinson (1990), from this literature a number of stylized facts emerged which are related to the import of intermediate inputs. First, countries undergoing ELG strategies have industrialized by achieving dramatical structural change characterized by among others a rapid increase in the use of intermediate inputs. Second, there is an associated transformation with industrialization which finds that there is a positive correlation between aggregate growth and TFP growth. Thirdly, the contributions of TFP growth to aggregate 3

4 growth are higher ELG countries than for other developing countries. More interestingly, the fourth stylized fact states that import substitution leads to lower TFP growth by reducing cost-reduction incentives. Alternatively, import liberalization and therefore export expansion increase TFP growth by relaxing the foreign exchange constraint, facilitating imports of intermediate inputs and capital goods (see also Silverstovs and Herzer, 2005). Another advantage of import liberalization is the technological externalities that arise from the imports of intermediate inputs and capital goods (Mody and Yilmaz, 2001; Lopez and Yadav, 2010; Acharya and Keller, 2008; and Kasahara and Rodrigue, 2008). Figure 1 shows the differences between the ELG regime and the ISI regime for the access to the pool of international knowledge. Figure 1: Trade regimes and the effects of imported and domestic machinery Source: Mody, A. & Yilmaz, K. (2001) Imported Machinery for Export Competitiveness, World Bank Economic Review These results have motivated a number of economists to incorporate these structural changes into growth models. This paper will give a summary of the literature of imported intermediate goods and other capital goods and how it changes theneoclassical growth models. In Section II, the paper examines the effects of imported intermediates on growth and total factor productivity. The effects will be described theoretically and empirically. In Section III, this paper analyzes the mechanisms through which the imported intermediates affect growth and TPF growth. Section IV poses other linking theory plus policy recommendations and this paper ends with a summary in Section V. 4

5 I. Intermediate Inputs The neoclassical assumption that input varieties are symmetric, differentiated horizontally, but not vertically, has to be redefined. There is a vast amount of literature that stresses the importance of gaining access to high-quality inputs on the import market, especially for developing countries. Kugler and Verhoogen (2009) draw on rich product-level information from Colombian manufacturing plants, to deliver a new set of facts about input varieties. They collected information from the Annual Manufacturing Survey and found values of each output and input of each plant in 4000 product categories. Their research started with stating that importers of inputs perform better than non-importers (See Table 1). In the first column of Panel C, Kugler and Verhoogen (2009) show that, while controlling for region, industry, year but not plant effects, importing plants significantly will experience a higher effect on TFP. Table 1: Plant-level variables versus Importer status Source: Kugler, M. & Verhoogen, E. (2009) Plants and Imported Inputs: New Facts and an Interpretation, American Economic Review 99 (2), p

6 Column 2 shows that, while keeping the same controls, this effect is not offset when these plants will also turn out to be exporting plants. To include the indicator for exporting plants affects the indicator for importing plants only slightly. However, columns 3 and 4 show an interesting result. In these columns, the plant effect is included and this affects the indicator for importing plants heavily, having the fact that the correlation between being an importer and TFP is not significant anymore. This suggests that the positive correlation experienced in columns 1-2 is due primarily to selection of high-productivity plants into importing. Having stressed the assumption that outputs and inputs are homogeneous in quality, while research suggests they are heterogeneous in quality, consequently can be misleading for the standard methods of estimating TFP and interpreting these results has to be cautioned. As shown in Panel D in Table 1, importers use more distinct categories of inputs and this holds even within plants, though for a smaller magnitude. This is consistent with the idea that importing increases the availability of different type of inputs (Kugler and Verhoogen, 2009). This is in line with the theory of Stone and Shepherd (2011), Caselli and Wilson (2004) and a comment on this by Kortum (2004), that states that the inputs are heterogeneous, and not homogeneous as posed in the neoclassical model. Dynamic gains Traditional trade models, such as the Ricardian model and the Heckscher-Olin, are based on gains from trade that arise from specialization by comparative advantage. These are often called the static gains from trade. These gains are called static as they are a one-off effect in improved efficiency. More recently however, attention has changed to understanding dynamic gains from trade. Early literature on understanding the dynamic gains from trade includes the relationship between variables that measure trade openness and GDP growth. A convincing result that supports the view of dynamic gains from trade is that a 1% increase in trade openness, defined as an increase in trade weighted to total GDP, boosts GDP per capita by approximately 1%-2% (Stone and Shepherd, 2011). Over the past few years the economic academic literature has turned away from the macrolevel literature of the link between openness and growth. More recent literature focuses on micro-level models, which take a different approach and find evidence for the link between trade liberalization and within-firm productivity gains. Here, firms are heterogeneous and 6

7 the mechanism suggests that less-productive firms exit the market due to increased competition arising from imports. This is followed by a shift of the resources to the more productive firms who can now produce more. The final result is that the sector in which the firms operate experiences an increase of average productivity. In other words, reducing trade costs promotes competition which has an effect on the reallocation of resources to more productive firm raising average productivity (Melitz, 2003). Stone and Shepherd (2011) and Goldberg et al. (2009a) find strong evidence that trade liberalization affects productivity positively. The latter does this by showing that the import of intermediate inputs and the availability of new inputs after trade liberalization and consequently, an extensive margin growth, adds significantly to manufacturing output growth in India. The former, however, tries to find what happens outside a specific trade liberalization episode, by measuring the impact of imported intermediates on TFP of firms. In this section, the paper will provide evidence that the dynamic gains from trade do contribute to TFP and output growth, whereas in the next section we will explain the mechanisms through which this happens. Stone and Shepherd (2011) provide evidence by running regressions separately for multiple sectors, respectively textiles, leather and garments, food and beverages, heavy manufacturing, electronics and light manufacturing. They find that the imported intermediates as a share of total input have a positive effect on TFP in all sectors except the textiles, leather and garments sector (see Table 2). The imports of capital goods have a strong impact in only two sectors, the textile sector and the food and beverages sector. Table 2: Firm-specific regressions; TFP versus imports of intermediates and capital goods Source: Stone, S.F. & Shepherd, B. (2011) The role of intermediate inputs and equipment imports in dynamic gains from trade, Globalization, comparative advantage and the changing dynamics of trade, Chapter 7, p

8 Furthermore, Stone and Shepherd (2011) state that the amount of imported intermediates in the textile sector is bigger than the amount imported in, say, the food and beverages sector. Yet, the indicator of food and beverages shows a relatively large effect of imported intermediate inputs on sectoral productivity, where the indicator of textiles, leather and garments is insignificant. The interpretation of these results is that it is not the volume of imported intermediates that determines the impact on productivity, but it is the function of the type of imported intermediate inputs. For example, the type of imported intermediates in the textile sector will have relatively small embedded technology, whereas in the food and beverages sector products such as fertilizer and high-yield crop varieties can have a large effect on sectoral productivity (see also Kortum, 2004). The differences of input types are used by Caselli and Wilson (2004) to account for large differences in TFP across countries. Caselli and Wilson (2004) look at disaggregated imports of various types of machinery and equipment to make three contributions to the respective literature. The first contribution lists remarkably large differences in investment composition, and more interestingly second, the differences are explained by each type s complementarity with other abundant factors differences across countries. Mainly and third, those differences in type of capital composition hold for large differences of TFP across countries. Theory According to Caselli and Wilson (2004) capital is heterogeneous, as opposed to in the neoclassical model. The following model delivers predictions on each type of capital. Now, imagine that in country i final output is produced combining a variety of intermediates,, according to a constant elasticity production function: (1) Production functions like equation (1) have been the staple of recent economic developments in economic growth theory. In this function, B is a disembodied TFP term dependent on the country-specific characteristics. Furthermore, the intermediate good is produced combining the factors of labor and capital: 8

9 0<α<1 (2) where is the labor used to produce intermediate good p and is the amount of capital used to produce p. is the productivity measurement of input p in country i. The interpretation that productivity parameter A is country and product specific is as follows; the equipment of type p is complementary with the endowments of country i. Here, one has to assume the law of one price holds, namely that the price of a commodity is equal across countries taking into account the exchange rate. Another assumption is that γ<1 implying that all these inputs are imperfect substitutes. Furthermore, labor is homogeneous within countries and perfectly mobile. The share of capital per country is important to learn about how varies across countries and accounts for cross-country TFP differences. Since the s are measured in dollars we can write: where is the dollar value of the capital stock, which is taken as given. Then, setting the marginal product of labor equal to the wage rate, setting the marginal product of capital equal to the rental rate of capital and incorporating that the capital-labor ratio is equalized among all sectors, Caselli and Wilson (2004) find that under the above assumptions in equilibrium: (3)This states that the share of capital p in country i relatively to the total capital share is related to the efficiency of p in country i relatively to the total efficiency of total capital in i. In other words, investment tends to concentrate on that type of capital, K, with the highest embodied efficiencies. However, this is partly counterbalanced by the diminishing returns to the intermediate inputs implied by the assumption γ<1. If =1, then the inputs would be perfect substitutes and all the investment in a country would be concentrated on the highest-embodied-effiency type of capital. In contrast, with imperfect substitutes, investors will be willing to hold a diversified portfolio of capital types. 9

10 Now, according to Caselli and Wilson (2004), there are country-specific factors that influence the demand for different types of capital. Following, what are these country-specific factors and do they show significant results? The general approach of estimating these factors will be to make assumptions on the determinants of the s, and test these assumptions by estimating equation (3). The country- and product-specific characteristics enter the model through the following equation: (4) where captures the values of characteristics c in country i relative to the average value of characteristics in the world. In other words, it captures the abundance of characteristic c in country i. captures the complementarity between characteristic c and the type of capital p. Caselli and Wilson (2004) find as a first characteristic human capital, this could be c. If δ=0, then there would be no complementarity between human capital and physical capital, implying that the production of that type of equipment only needs physical capital. However, if δ is large then capital type p is high-complementary with human capital. Hence, it is a high-skilled type of capital. Other characteristics are inward foreign direct investment (FDI) and outward foreign direct investment, where a high δ combined with the former would imply a comparative advantage by foreign firms in importing and installing this type of equipment, whereas a high δ combined with the latter could imply a transfer of knowledge into the country which is complementary with the regarding type of capital. Furthermore, a high δ when the c represents the degree of property rights protection denotes higher profitability of investment when property rights are better protected. Next, the share of government spending related to this type of capital as a ratio of GDP, in combination with a high δ, would imply that the regarding government has a comparative advantage in, or a unique demand for this type of capital. A high δ for measurements of financial development could denote that external investing is an important aspect of the type of capital. Lastly, Caselli and Wilson (2004) consider geographic characteristics, where a high δ could account for differences in transport costs across countries for different types of capital. Caselli and Wilson (2004) estimate the effect of the different characteristics by obtaining raw data for imports and exports for over 100 countries. Furthermore, they aggregate capital 10

11 imports in 9 different capital-type categories to match the 9 capital-producing industries. These are fabricated metal products, non-electrical equipment, office, computing, and accounting machinery, electrical equipment (excluding communications equipment), communications equipment, motor vehicles, other transportation equipment, aircraft, and professional goods. For example, intermediate inputs or capital goods in this type of industry are hardware in the fabricated metal products industry, and radar equipment in the communications equipment industry. Table 3: Embodied R&D regressions Source: Caselli, F. & Wilson, D. J. (2004) Importing technology, Journal of Monetary Economics 51, p. 23 The results of complementarity between those variables and the investment decision in a type of capital good are as followed and are modeled by an interaction term between the concerning variables and R&D content of the type of capital (see Table 3). Note, the log( ) variable denotes the log of an equipment type s relative R&D intensity (relative to metal products). The interaction term between inward FDI and the R&D intensity is negative and this result is robust. This is inconsistent with existing literature which states that FDI is an important source for technology transfer. However, it is consistent with the 11

12 view that inward FDI outsources the production of low-technology goods to countries with cheaper inputs. Besides, outward FDI is associated positively with the investment decisions in capital imports, possibly covering for the transfer of knowledge acquired by the use of more high-tech capital imports. The protection of property rights robustly and positively interacts with the R&D content of types of capital. Another robust indicator is the interaction term for geographic measurement, more specifically remoteness. The positive coefficient implies that places further away import a relatively larger share of high-tech capital. Possibly, because high-tech types of capital are physically lighter. Next to remoteness, other geographic barriers to the trade of intermediates reflect costs arising from marketing overseas, negotiating a foreign purchase, transporting goods over the borders, tariffs and other non-tariff barriers, distributing the goods in foreign markets and adapting the equipment to the standards of these markets, installation in foreign production and training the workers to use this equipment and lastly, providing parts, maintenance and customer service from abroad (Eaton and Kortum, 2001). The other variables give evidence of possible negative or positive relationships, though they are suggestive but not conclusive. An interesting result though is the robust negative coefficient of the log( ) variable. This suggests that for a country with average characteristics, capital goods embodying a relatively larger share of R&D are less efficient. However, the positive coefficient of the time trend shows that the efficiency of high R&Dintensive capital goods is catching up with the efficiency of less R&D-intensive equipment. Next, we will show whether R&D-intensive capital goods imports and imported intermediates matter for explaining productivity and growth differences. Evidence We now showed that capital goods and intermediate inputs are heterogeneous and that these goods are complementary with country-specific characteristics in specific industries. We have found that there are a number of determinants that have a significant effect on the investment (imports) of R&D-intensive capital goods. Furthermore, we have concluded that because of more complex assumptions, we cannot estimate the models by using simple 12

13 standard models. Now, we examine the evidence in the literature whether the import of capital goods increases productivity and has a positive effect on growth. As shown previously, FDI is associated with low-tech imports and high-tech imports. Marwah and Tavakoli (2004) actually investigate the effect FDI has on the growth of the productivity of total capital, by the use of estimated time series of years for four Asian countries Indonesia, Malaysia, the Philippines, and Thailand which have undergone significant changes in the late 70s. Barriers to trade and barriers to foreign investment were either modified or eliminated, rules and regulations for foreign investment were relaxed and the role of government intervention was declined. Moreover, incentives to invest were stimulated. Marwah and Tavakoli (2004) find that for every 1% economic growth point the growth of total capital stock (domestic plus foreign) generated in Indonesia, in Malaysia, in the Philippines and in Thailand. Furthermore, the foreign capital stock, which is calculated by the FDI inflow minus the FDI outflows, has a significant contribution in this; is the share in Indonesia that accounts for 1 growth point generated by the growth of total capital. This is in Malaysia, in the Philippines, and in Thailand. Thus, FDI is not only complementary with low- and high-tech imports; it also has a significant contribution to the growth of GDP. Next, we have to show whether the import of capital goods and intermediate inputs have a positive effect on productivity, hence growth. Another example of an Asian country that experienced trade liberalization, although later in 1991, was India. India s trade regime was amongst the most restrictive in Asia with an emphasis on import substitution combined with high tariffs and non-tariff barriers. After the abandoning of the restrictive trade policies, India experienced a growth in imports, dominated by an increase in intermediate inputs. Goldberg et al. (2009a) examines this growth of imports by studying the intensive and extensive margin (see Table 4). The intensive margin represents the growth in HS6 products that already existed in the previous period, whereas the extensive margin represents the growth in products that did not exist in the previous period. Interestingly, final goods imports have increased 90 percent over the period of , while the imports of intermediate inputs have increased 227 percent over the same period. Another interesting fact is that the contribution of the 13

14 extensive margin accounted for 66 percent to the overall growth of imported intermediate inputs, albeit the contribution of the intensive margin accounted for one-third. Table 4: Decomposition of Import Growth, Source: Goldberg, P., Khandelwal, A., Pavcnik, N. and Topalova, P. (2009a) Imported Intermediate Inputs and Domestic Product Growth: Evidence from India, CEPS Working Paper No. 192, p. 34 Thus, the growth of imports in India was dominated by the growth in new varieties of intermediate inputs and capital goods. According to Hasan (2002) these new intermediate inputs and capital goods embody new technologies (embodied technology), which could have an impact on the productivity of India. Furthermore, literature suggests that there is a significant positive relationship between technical knowledge (disembodied technology) and productivity. Hasan (2002) estimates this impact on the productivity of Indian firms using panel data and makes a clear difference between embodied technology and disembodied technology imported by Indian firms. Moreover, Hasan (2002) analyzes the manner in which foreign and domestic technologies interact with each other in production.table 5 shows the results of the effects of domestic R&D capital (R), imported disembodied technology capital 1 (T), technology embodied in imported capital goods ( /K) and technology embodied in 1 This involves the supply of designs, blueprints and technical assistance by foreign firms to domestic contracting firms 14

15 domestic capital goods ( /K) on the dependent variable, which is the productivity of Indian firms. They divide the firms in three sub-samples; scientific firms, non-scientific firms and technology-intensive firms. Table 5: Fixed effect model with AR1 correction Source: Hasan, R. (2002) The impact of imported and domestic technologies on the productivity of firms: panel data evidence from Indian manufacturing firms, Journal of Development Economics 69, p. 37 The coefficients of R give insignificant results, however the coefficients of T do present significant and positive results implying that investment in disembodied technology will be productive if the investments are foreign in origin. This is consistent with the findings of Marwah and Tavakoli (2004) that FDI has a positive effect on the growth of GDP. Furthermore, not only were intermediate inputs and new capital goods dominant for the growth of the total capital stock (Goldberg et al., 2009a), but also over and above this impact new imported intermediates and capital goods impact productivity positively (Hasan, 2002). However, this impact is only significant for the firms operating in the technology-intensive industries. Conversely, the impact of the domestically produced new capital goods on productivity is broader and they positively affect all three sub-samples. The reason behind that imported capital goods have their largest effect on productivity in the technology-intensive firm industries is that in those industries India is lagging behind developed countries. Hence, the 15

16 technology-intensive industries have more to benefit (marginally) from foreign technology embodied in imported capital, or alternatively foreign technology is more transferable in these industries. Table 6: Interaction term between foreign and domestic capital goods Source: Hasan, R. (2002) The impact of imported and domestic technologies on the productivity of firms: panel data evidence from Indian manufacturing firms, Journal of Development Economics 69, p. 43 More puzzling is the fact that domestic capital allows for a significant positive impact on productivities across all sub-samples. One reason for this phenomenon is that the new capital domestic product embody superior foreign technology, i.e. import may enable producers of domestic capital to incorporate superior technologies in their products that will enhance productivity. Hasan (2002) provides support for the fact that imports enable producers to incorporate productivity enhancing technologies. Table 6 includes interaction terms to find the relationship between domestic capital goods and foreign imported capital goods. A positive interaction term between two production factors, for example labor and capital, refers to a complementary relationship between the two factors. A negative coefficient however, implies that the two factors have a substitute relationship, meaning that an increase in labor, would cause a decrease in the output elasticity of capital. In other words, if a significant amount of labor was needed to utilize capital, this would show itself in a positive interaction term. To relate back to the imports of intermediate and capital goods, we expect a positive sign for the interaction term with domestic capital goods, and this is actually the case (significant positive coefficient in all sub-samples) implying that imported capital goods and domestic capital goods are complements in production (see Table 6). This can be explained knowing the fact that India s government policy only allowed capital imports when 16

17 there were no existing domestic substitutes. Nonetheless, the positive coefficient denotes that firms should invest in both domestic and foreign capital to be most productive. The assumption that domestic and imported inputs are complements is in line with the existing endogenous growth theory, and this assumption is crucial (Romer, 1994). Indeed, such an assumption is crucial in these models because it provides a link whereby barriers to trade lead to inefficiencies in the accumulation of capital and ultimately tie an economy down to a lower equilibrium growth rate (Hasan, 2002, p. 43). The manner in which imported inputs affect domestic inputs will be described in the next section. Supplementary evidence of the effect of intermediate inputs and imported capital goods on productivity and growth is presented by Kasahara and Rodrigue (2008). Kasahare and Rodrigue (2008) estimate the effect of imported inputs on a plant s productivity by switching from being a non-imported to an importer of intermediate inputs. The results show that to switch to being an importer improves productivity immediately. A positive effect is estimated substantially across different estimators, though even with the Within- Group estimator, which one may believe is downwardly biased, they find a positive result of 2.6%. This means that importing intermediates or capital goods has a 2.6% effect on productivity. Furthermore, Kasahara and Rodrigue (2008) find evidence for a positive dynamic effect from the use of imported intermediates, which this paper will elaborate on in the next section. Theory predicts that this effect is to be on productivity for less developed countries (LDCs), but not for developed countries, because the latter has a comparative advantage in the production of capital goods, intermediates, equipment and machinery. Mazumdar (2001) estimates this theory and finds that poor countries gain more from imported capital than rich countries do. Lopez and Yadav (2010) find a positive correlation between productivity and the import of intermediate inputs (Table 8). Mastromarco and Ghosh (2009) find that imported capital goods and R&D, and FDI are important channels of increasing productivity. Colantone and Crino (2011) find that imported inputs have a positive, and generally sizeable, effect on productivity, through static gains from trade and through dynamic gains from trade. 17

18 II. Mechanisms In the previous section was stated that the import of intermediate inputs generates not only static gains from trade, but also dynamic gains from trade. This section examines through which mechanisms the import of intermediate inputs can generate dynamic gains from trade. This paper has discussed the transfer of knowledge and the effect imported capital products have on domestic products. However, what are the conditions under which imported intermediate inputs enhance dynamic gains from trade, hence TFP growth and GDP growth? Dynamic gains from trade Through the rapid growth of the newly industrialized countries (NICs) in the last past decades, other developing countries were inspired to actively liberalize their restrictive trade policies. LDCs focused more on export regimes and import liberalization which inclined the imports of capital goods and intermediate inputs. This paper showed empirically that there is a positive effect between imported intermediate inputs and growth, and that this is caused by among others dynamic gains from trade (Stone and Shepherd, 2011; Goldberg et al., 2009a). The question still to be answered is what mechanism leads to dynamic gains from trade. The first factor to be examined is the transfer of technical know-how. Kasahara and Rodrigue analyze whether and how the transfer of technical know-how can lead to dynamic gains from trade. Through adoption and imitation of imported technologies, countries can take advantage of research and development (R&D) abroad to improve the efficiency of domestic production (Kasahara and Rodrigue, 2008). The technologies that are imported are embedded in intermediate inputs and capital goods. As discussed earlier, there exists a positive dynamic effect from the use of imported intermediate inputs. The evidence suggests that the past import status (see also Lopez and Yadav, 2010) has an effect on current TFP, i.e. there arises learning from importing. The data set covers all plants with more than 10 workers in Chile for the period The econometric specification of the research by Kasahara and Rodrigue (2008) is as follows: (5) 18

19 where lowercase variables imply log values of capital (K), skilled labor (, unskilled labor (, energy inputs (E), intermediate goods (x), past import status (d) and the variable of interest,, which represents a serially correlated productivity shock. are the unforeseen shocks to plants at the time of the input decisions. To analyze the effect of the past import status on productivity by means of learning from importing one has to specify by the following stochastic process: (6) where is a year-specific productivity shock and is statistically independent with and according to an accumulative distribution. Kasahara and Rodgrigue (2008) consequently estimate the coefficients for γ and ρ, where a positive value for γ provides evidence for the learning by importing. Table 7 shows the results for γ and ρ using GMM estimation and OP/LP estimations for the basic sample and the extended sample. The estimated values for γ are positive and two out of four times significant. These positive values suggest a learning effect through importing, although the evidence is not as strong. The long-run dynamic effect of the use of imported intermediate inputs is measured by. Table 7: Estimates of γ and ρ Notes: Standard errors are in parentheses. Columns 3-4 use the Basic Sample which excluded plants for which the initial capital stock is not reported. Columns 6-7 use the Extended Sample for which the missing initial capital stock is imputed with projected initial capital stock based on other plant observables. The System GMM estimator in columns (3) and (6) use a lag length of 2 and 3 for instruments in the first-differenced equations and a lag length of 1 in the level equations. Source: Kasahara, H. & Rodrigue, J. (2008) Does the use of imported intermediates increase productivity? Plant-level evidence, Journal of Development Economics 87, p

20 The OP/LP 2 estimator shows that the long-run effects of a 100% decrease in the use of domestic intermediates are approximately 17% and 20%, respectively for the basic sample and the extended sample. This implies that the higher the share of imported intermediates to domestic intermediates, the larger will be the productivity effect from importing (Kasahara and Lapham, 2007). According to Acharya and Keller (2008) there exist two channels through which the liberalization of imports affect productivity and consequently the net effect can be positive or negative. The two channels are defined by technological externalities (the learning effect) and by the selection effect. As previously shown, the average productivity is enhanced through the reallocations of resources to more productive (heterogeneous) firms (Melitz, 2003). This selection effect allows for two effects, the positive selection effect and the negative selection effect. The positive effect is, as described above, the rise in average productivity through the reallocation of resources to more productive firms. The negative effect arises because through the new import competition it is more difficult for, especially the more-productive, firms to compete abroad. Thus, the profits of those firms will decline and consequently market shares will shift to less-productive firms, and relatively weak firms start operating. In the long-run this effect dominates and import liberalization lowers domestic productivity if it outweighs the effect from technological spillovers. In the shortrun however, the positive selection effect dominates, because in the short-run the number of domestic and foreign firms does not respond much to the increasing competition. Concluding, if imports are technology-intensive capital goods or intermediate products, then this can outweigh the negative competition effect, inducing a positive effect on productivity in the long-run. Lopez and Yadav (2010) contribute to the spillover literature by stating that importing spillover effects are strongly localized. Firms that operate in the same region are more likely to be importers. Thus, the effect of spillovers of imported intermediate inputs on the labor market is estimated using plant-level data from the manufacturing sector of Chile for the period , which covers all manufacturing plants with 10 workers or more. Table 8 shows the main results. First, there is evidence consistent with the earlier finding that past 2 The OP/LP estimator is used to control for simultaneity and self-selection, so is the GMM estimator. However, there are caveats regarding the validity of both the OP/LP estimator as well as the GMM estimator, hence we take the results with caution. 20

21 import status is important for importers. Though, Lopez and Yadav (2010) suggest that sunk costs of importing intermediate inputs may be important, at least in the case of Chile. When a firm decides to start importing it has to look for suppliers and scan the international market for low-cost inputs. In other words, the firm generates costs when it starts importing. If a firm stops importing and later decides to start again it may have to pay these costs again. This can be an important source for the persistence of importing intermediate inputs. Furthermore, the observation can be made that firms that pay higher wages are more likely to import, suggesting that skill-intensive plants are more likely to import intermediates and capital goods. The main result to derive from Table 8 is that the fraction of importers in a region, regardless of industry they operate in, has a positive significant coefficient implying that this has a positive effect on the probability whether firms will import or not. This suggests the existence of importing spillovers in the manufacturing sector in Chile. Table 8: The import decision probit model Source: Lopez, R.A. & Yadav, N. (2010) Imports of Intermediate Inputs and Spillover Effects: Evidence from Chilean Plants, Journal of Development Studies 46 (8), p

22 Domestic incentives to import intermediates are important for the enhancement of productivity. Table 8 shows that next to regional spillovers, other factors affect the decision to import. Plants that are exporting plants, have a foreign ownership or own foreign technology licenses are more likely to import (Lopez and Yadav, 2010). Besides domestic incentives there is another condition that is important for the generation of knowledge spillovers. According to Mody and Yilmaz (2001), the relative importance of technological knowledge spillovers will change as domestic incentives and absorptive capacity evolve. Rate of adoption Most of the technologies imported to LDCs originate in advanced countries and are adopted there first. Subsequently, these technologies trickle down to less-developed countries. The speed or rate at which this trickle-down diffusion happens is conditional on the absorptive capacity of those countries. According to Comin and Hobijn (2004), the rate of adopting new technologies depends on some important determinants. The most important determinants are human capital endowment of a country, the type of government, degree of openness to trade and adoption of predecessor technologies. Mastromarco and Gosh (2009) assign a big role to human capital, which can help explain an economy s capacity to absorb new technologies. Comin and Hobijn (2004) use a panel data set consisting of 25 major technologies in 23 countries over a period of 200 years, i.e. for every piece of technology they have information about variation in adoption across both countries and time. Comin and Hobijn (2004) compare rich countries (leaders) with poor countries (followers), and furthermore differentiate between technologies that took a relatively long time to adopt and technologies that were adopted quickly. Considering these two dimensions is of interest, because the former can help explain the role of technology adoption in dispersion of income levels across countries and the latter can help explain convergence patterns. Next, this paper describes main theories of technology adoption and diffusion distinguished in the article of Comin and Hobijn (2004). First, there is vintage capital theory. Most vintage models assume that countries only invest in the frontier technology. This means that when a new vintage is introduced, there will be no investment anymore in old vintages, hence the part of the net capital stock embedded 22

23 with these old vintages will decrease through depreciation. Many technologies, however, have very long implementation lags. Differences in these lags across countries could explain the disparities of technology adoption across these countries, though the vintage capital theory assumes these lags to be zero and thus fails to capture this important fact. Second, related to vintage capital theory is vintage human capital theory. Both these models have in common that implementing a technology results in technology specific experience, which is called vintage human capital. Vintage human capital theory, importantly, intend to explain the differences in adoption lags we observe across countries, which are not captured by the standard vintage capital model. Vintage human models can help explain the delays of adopting new technologies that replace old ones that led to the accumulation of technology specific human capital. The acquisition of a technology specific skill-set, namely, will reduce the incentive to adopt new technologies and, consequently, workers and plants will remain to invest in old technologies even though new and more efficient technologies exist. Another fact not explained by the standard vintage model is that the economic leaders tend to innovate and are the early adopting countries, whereas the economically lagging countries mostly imitate. This is captured by the innovator-imitator models. An imitating cost results in the imitating country persistently lagging behind with the adoption of new technologies. Next, there is a model on the diffusion of General Purpose Technologies (GPTs) that can help explain adoption disparities. These are technologies which have wide economic effects. This model states that the countries that can adopt the GPTs with the least expenditures on complementary inventions and the countries that expect the biggest demand shift after implementing the GPT are the early adopters. Countries that need more complementary innovations will experience a delay relative to the early adopters. All these models fail to include empirical variables that explain the disparities of technology adoption. Comin and Hobijn (2004) suggest a couple of candidates for these variables. Above all, they consider factor endowments that possibly affect the rate of technology adoption, namely human and physical capital. These factor endowments may affect the speed of adoption in the following three ways. If technology and the factors of production are complementary, then countries with high levels of human and physical capital would adopt 23

24 first. If technology and these factors are substitutes, then firms would have higher incentives to invest in factor savings technologies if the price of that factor is high. Lastly, they suggest a model of appropriate technology, claiming that new technologies can only be adopted with the appropriate portfolio of human and physical capital endowments. However, factors endowments alone are not the whole story. Further variables that may affect the rate of adoption are trade, vested interests and institutions. Trade possibly affects this through two channels, the push and the pull effect. The push effect states that imports of intermediate goods or capital goods which embody technology tend to push the knowledge down the trade channel. These are known as the spillover effects elaborated on earlier in this paper. On the other hand, the pull effect arises from the shift from domestic protective policies to more productive policies after trade barriers are lifted. Subsequently, when the barriers are lifted domestic producers get more involved in productive innovative activities that are necessary to sustain their international competitiveness. International competing, and thus importing technology to sustain the competitiveness, creates winners and losers. Labor saving technologies are repelled by displaced workers who try to prevent these technologies from being imported. Political interest, e.g. colonial ties, is another example how vested interest can affect the speed of adopting technologies. Furthermore, the legislative power of an economy to protect property rights and these vested interests possibly affect the rate of adoption. Institutions therefore play an important role in explaining the disparities between the rates of adoption across countries. Comin and Hobijn (2004) estimate the effects of this broad number of variables on the rate of technology adoption. In Table 9, the regression results are summarized. The first component that contains valuable information is the real GDP per capita coefficient which predicts a significant effect on the speed of adoption, namely a 1% higher standard of real GDP per capita infers that this country is 1% further in the rate of adopting technologies. The regression results also show that education matters, though it is not primary enrollment that matters but secondary enrollment, and secondary enrollment before 1970 turns out to matter much more than after

25 Table 9: Pooled regressions on the rate of adoption Standard error in parentheses. *Significance at 1% level ᵃInstrumented for with 5-year lagged values. Source: Comin, D. & Hobijn, B. (2004) Cross-country technology adoption: making the theories face the facts, Journal of Monetary Economics 51, p

26 The former is because the skills required for imported technology go beyond primary school skill sets and for the latter it seems that after 1970 attainment rates are more important, especially tertiary attainment rates which is consistent with the view that modern technologies are complementary with college level skills. Trade has an effect on the rate of adoption, when we consider the variable openness. More interestingly, countries whose trade makes up a larger share of their GDP turn out to be more ahead in the process of adopting foreign technologies. Trading with more advanced partners generates knowledge externalities that speed up the adoption process. Next to the positive effect of the larger share of trade, institutional variables have an impact. Group D in Table 9 shows six institutional variables. The first three have to do with the type of regime, namely whether the effective executive is a monarch, a premier, does not exist or does not hold a formal government post. An executive structure is important for the enforcement and protection of property rights, and we can see that when there is no effective executive this has a negative effect on the rate of adoption. If there is a military regime, the negative effect is even stronger. Another channel through which institutions can have an effect is the legislative power of a country. If there is strong legislative power to protect vested interests this has, not surprisingly, a negative effect on the adoption rate. Finally, the last variable describes that when the parliament is more fractionalized, this has a positive effect, however we have to be cautious interpreting this because the most observations are postworld war II. Finally, Table 9 shows evidence that the adoption of a previous technology has a positive effect on the adoption of a new technology. Hence, leaders in the adoption of old technologies are likely to be leaders in adopting the new technology. This goes against the theory of vintage capital, which predicts the existence of leapfrogging. Comin and Hobijn (2004) showed that human capital helps in explaining the economy s capacity to adopt new technologies. Additionally, Mastromarco and Ghosh (2009) find that FDI, imported intermediate and capital goods and imported R&D have a positive effect on productivity and more interestingly, that these effects depend strongly on the human capital accumulation. There is strong evidence that developing countries differ with respect to the efficient use of Frontier technologies, in which human capital accumulation plays a 26

27 significant role. The research of Mastromarco and Ghosh (2009) adds that human capital can significantly increase the effect of imported R&D when the level of human capital is high, however when the level is low R&D imports become insignificant. Furthermore, Xu and Chiang (2005) find that countries with a larger technology gap against the US technology tend to grow faster in TFP (convergence literature), and that the speed at which these countries catch-up increases with the level of human capital. Another important measure of human capital which we have seen before in this paper is learning by doing. Mastromarco and Ghosh (2009) show that FDI and imported capital goods and intermediate inputs have an increasing effect on productivity in the presence of learning by doing. This supports the view of complementarity between human capital and the rate of adoption of a country. The absorptive capacity of countries provides a useful explanation for the disparities in productivity. This is indicative for example, the Asian growth miracle and the African growth puzzle. Asian countries performed well and the literature stresses that outward orientation, sound macroeconomic policies and investment in human capital were the most important elements. On the other hand, Devarajan, Easterly and Pack (2011) show that private and public investment in Africa it not productive, which means there is not a favorable climate for human capital investments implying a slow rate of adoption in Africa and high inefficiencies. Effect of intermediate inputs on domestic products According to the endogenous growth literature (e.g. Romer, 1994) new products play an important role in economic growth. This literature has long identified that upgraded goods and new goods are a crucial driver of economic growth. There are theoretical contributions which state that imported intermediate inputs help countries to introduce new goods and through this channel intermediates can generate dynamic gains from trade and hence, boost economic growth.(goldberg et al., 2009a; Goldberg et al., 2009b; and Colantone and Crino, 2011). Goldberg et al. (2009a) find that approximately 25 percent of total manufacturing output growth could be explained by the creation of new domestic products, while at the same time access to imported intermediate inputs turned out to be potentially important for economic growth. Colantone and Crino (2011) try to find the contributions of new imported 27

28 intermediates to product innovation and through which channels new imported intermediate inputs stimulate domestic product innovation. Furthermore, they compare the new products characteristics with the old products characteristics. Colantone and Crino (2011) use a panel data set containing all EU countries except Cyprus and Malta over the period The model defines a product as new when the first domestic firm starts producing it and it estimates whether imported intermediates boost domestic product innovation and the economic magnitude of this effect. The respective model used to estimate the effect of imported inputs on product innovation is specified as followed: (7) where is the coefficient of interest. Furthermore, are country-industry specific effects, are year effects and is the error term. NP is the share of new domestic products to total domestic products, and NII is the share of new imported input varieties to total imported input varieties. The results of equation (7) are presented in Table 10. Columns (1)-(3) estimate equation (7) by OLS 3 at three different levels of aggregation of industries, where Column 3 represents the highest level of aggregation. Table 10 shows that the share of new imported intermediate input varieties is significantly associated with an increase in the share of new domestic products. Furthermore, the coefficients roughly double each time the aggregation level becomes higher, implying that not only do firms source inputs in their own industries, but also in other industries in the same aggregate group. To account for backward linkages across industries the next model is used: (8) 3 Colantone and Crino (2011) check for robustness of these results by accounting for outliers, using alternative definitions of the regressor, addressing concerns with the variables using dependent variable, constructing values, adding controls and lags and exploring heterogeneity. Furthermore, they cover for possible endogeneity by using IV regressions and to exploit trade shocks over the sample period. This, however, does not change the results. 28

29 This overall indicator covers all aggregated industries, therefore allowing for backward linkages across the industries. Table 10 shows that a 1 percentage point increase in this overall indicator is associated with a percentage point increase of new domestic products. Table 10: New imported inputs and increasing product innovation Source: Colantone, I. & Crino, R. (2011) New Imported Inputs, New Domestic Products, Development Studies Working Papers No. 312, p. 40 Colantone and Crino (2011) furthermore calculate the economic magnitude of the effect new imported input varieties have on new domestic products by estimating the following model: (9) CNP represent the contribution of new products to economic growth. Equation (9) predicts that a 1 percentage point increase in the overall amount of new imported inputs will enhance the contribution of new domestic products to growth with percentage point. 4 Colantone and Crino (2011) also find that the average rate of entry of imported 4 The standard error of this coefficient is (0,114) indicating a 1% significance level for this coefficient. 29

30 intermediates is 13,2% per year and that the contribution of new domestic products to growth is 24,8% (this percentage number is consistent with the findings of Goldberg et al. (2009b) who find roughly 25% for the contribution of domestic products to growth). Multiplying the average yearly entry rate with the estimated coefficient of equation (9) we obtain that new imported input varieties account for approximately one-fourth of the total contribution of new domestic products to economic growth. The results, though, are not conditioned on the substitutability of imports and,according to Goldberg et al. (2009b) the importance of new imported input varieties will decrease if the elasticity of substitution of the varieties is high. Next, this paper discusses through which channels new imported intermediates stimulate domestic product innovation. Colantone and Crino (2011) analyze three mechanisms, namely the expansion in the number of available intermediate inputs, access to cheaper inputs and access to higher quality inputs. Interestingly, the first mechanism appears to be statistically irrelevant. The other two mechanisms however are relevant. The first effect that access to cheaper inputs increases new domestic products is positive and significant, implying that the effect of new imported intermediates grows stronger with the relative price. Kugler and Verhoogen (2009) suggest that quality differences between domestic and foreign inputs are most plausible and parsimonious in explaining higher prices for imported inputs compared to domestic inputs. Second, Colantone and Crino (2011) explore the effects of quality differences on new product innovation and the effect of prices on new imported inputs conditional on quality differences. First, the effect of new imported inputs on new domestic products grows stronger as the quality of the imported inputs increases. Next and more interestingly, after controlling for relative quality the effect grows stronger the lower is the relative price of imported intermediates. The main assumption here is that higher prices are a signal of higher quality. Finally, they compare the characteristics of the new products with the old products in terms of volumes and prices, and they analyze how the differences depend on the use of imported intermediate inputs. The quantity of new goods sold relative to existing products is lower, and this is hardly influenced by the increasing new imported inputs. On the contrary, as new imported inputs increase, the price difference between price of new 30

31 products and existing products will increase, where new products are priced higher. Furthermore, if an industry relies on the imports of intermediate inputs, new domestic products exhibit a quality premium. Not only imported intermediates have an effect on domestic product scope, but also tariff reductions increase the product scope (Goldberg et al., 2009a). The paper will examine tariff reductions next. Effect of tariff reductions Till the 1990s many governments of developing countries were operating protective policies, including tariffs and other non-tariff barriers, quotas and ISI strategies. In the 1990s however, a new era of globalization was about to begin, the Washington Consensus (WC) was initiated. This consensus consisted of ten reforms 5 of which, among others, trade liberalization and openness to FDI were important policies to sustain, promote or ignite growth and increase incomes. Two decades later, there are many opposing views to the WC and moreover, according to Rodrik (2006) the Washington Consensus is dead. The view that policies matter is no more, the view that matters is getting the institutions right. Estevadeordal and Taylor (2009) tackle his statement that the WC is dead and try to prove by theory and empirically that trade liberalization can promote growth. Even so, in this paper has been shown that access to foreign intermediate inputs leads to dynamic gains from trade, hence increasing productivity and economic growth. One channel of which this access can be granted is the elimination of trade barriers, or in other words reductions in input tariffs. Estevadeordal and Taylor (2009) start by developing a basic growth model, then simulating this model and finally trying to prove the theoretical results empirically. The next part in this paper will follow their line of work. One may start by assuming a small developing economy, where developing is defined as an importer of capital goods and intermediate inputs. Furthermore, assume uniform factor intensities. Output is made by using two factors of production, labor and capital. Output is used as consumption, as a domestic non-traded intermediate input variety, as a non-traded 5 The ten reforms can be summarize as: fiscal discipline, reorientation of public expenditures, tax reform, financial liberalization, unified and competitive exchange rates, trade liberalization, openness to FDI, privatization, deregulation, and secure property rights (Rodrik, 2006). 31

32 capital good or it is exported to pay for imports of capital goods and intermediate inputs. Labor endowment, L=1, is fixed and capital, K, can be accumulated. The Solow Version will be analyzed, and the Ramsey version is used to verify. The model uses a Cobb-Douglas production function, including intermediate inputs, X: (10) Given the Cobb-Douglas production function, spending on intermediate inputs is σy and value added is (1-σ)Y. Output is the numeraire and its price is equal to 1. Furthermore, transport costs are assumed to be zero, trade is balanced, and units are chosen so that world prices of imports are also equal to 1. The domestic price of capital goods, I, is = (1+ ) and the domestic price of imported intermediate inputs, X, is = (1+ ). Estevadeordal and Taylor (2009) examine two extreme cases in order to check the sensitivity of growth to reductions in tariffs. Case 1 assumes that all I and X goods are traded and can be imported and that domestic production can only be used for consumption. This will lead to a full pass through of tariff reductions to the domestic price of inputs. The second case assumes that there is a limited pass through of tariff changes to the domestic price because only a fraction of I and X is traded. The rest is non-traded and used for domestic output production. Firstly, consider case 1. In the Solow model spending on intermediates is σy= and spending on investment is =, where s is the exogenous savings rate. Hence, consumption is equal to. Substituting in equation (10) for X gives: (11) From equation (11) is derived that a fall in, which means a fall in, is isomorphic to a rise in TFP. This is, which is explained before, where dynamic gains from trade are created through the imports of intermediate products. Estevadeordal and Taylor (2009) then 32

33 proceed by calculating the steady state level of capital, beginning with the dynamic equation for capital: The condition for the steady state is that investment is equal to depreciation: Substituting for Y, implies that: Now, calculating the steady state of capital gives: Hence, the steady state of capital is: (12) From equation (12) one can derive that not only intermediate inputs have an isomorphic effect on growth, but also imports of capital goods can create dynamic gains. The isomorphic effect of intermediate inputs has an effect on the steady state level of capital and a fall in the tariff rate for capital goods is isomorphic to a rise in the savings rate.. Estevadeordal and Taylor (2009) now simulate the first case where all goods are traded to obtain a high estimate for long-run growth. For both cases, the parameters are used in order that they are representative for developing countries. Furthermore, the parameters used in the model of Estevadeordal and Taylor (2009) are representative for this model only, more specifically for equations 10 up to and including 14. The model sets α = 1/3 and assume that s = 0.25 and δ = Furthermore, σ = 0.50 and in the case of fully traded inputs β = 0.3 and 33

34 γ = 1. In the first case the Ramsey model is identical to the Solow model, except that it uses an endogenized savings rate. For the simulations of the Solow and the Ramsey model in the first case, the final steady state per year is calculated starting from an initial steady state with which means there is a 25% ad valorem tariff on intermediate inputs and on capital goods. Three types of simulations of trade liberalization are considered: First, an elimination of the intermediate input tariff, setting second, elimination of the capital tariff, setting and last, eliminating both tariffs and thus reducing both and to 1. The simulations are projected in Figure 2. Figure 2: Growth simulations when all goods are Traded Source: Estevadeordal, A. & Taylor, A.M. (2009) Is the Washington Consensus Dead? Growth, Openness, and the Great Liberation, 1970s 2000s, IDB Working Paper Series I38, p. 49 Figure 2 shows, as expected, that the Ramsey model has a faster convergence speed than the Solow model. For the rest of the results, the two models show the same effects. A 34

35 reduction in the tariff on capital goods (Simulation I) has no immediate impact, as we have shown this only affects the steady state level of capital and thus encourages capital accumulation. In the long-run this raises output with approximately 11% (this we can read from Figure 2). However, a reduction of the tariff on imported intermediate inputs (Simulation X) has an immediate effect, since this raises productivity right away as seen in equation (11) and input tariff reductions also encourage capital accumulation. In the longrun output rises by roughly 40%. Finally, when both tariffs are removed (Simulation XI), both the effects are compounded and this results in a long-run growth of roughly 56%. This is the high-estimate. Next, this paper will consider the second case of Estevadeordal and Taylor (2009) stating that most of the goods are non-traded and estimating the low-estimate. In general, one may assume a Leontief technology assumption which allows for how far intermediate input complementarities can enlarge these development frictions. Another assumption is that the investment function and the intermediate function are Leontief composite of non-traded goods, N, and traded goods, T, implying that these goods are complements, which is consistent with the view of Hasan (2002). Hence, there is no pass through from tariff reductions to the prices of non-traded capital and intermediate goods. This gives the following aggregate functions for investment and intermediate inputs: Since the domestic output price is equal to 1 and this can be used as the non-traded good, the price indexes for one unit of investment and one unit of intermediate input are then and respectively. Here represents the share of non-traded goods times the domestic output price (which is 1), and represents the share of the traded goods times the price of investment (intermediate inputs). The analysis now goes as before, resulting at a steady state of capital where there is less trade: (13) 35

36 The Ramsey model differs from the Solow model in the way that it uses an endogenized savings rate instead of a fixed savings ratio. This gives the following steady state of capital: (14) An important comparison between the Solow and the Ramsey model is that the elasticities with respect to the price of capital and the price of intermediate inputs are equal. The differences between these models are the transitional dynamics. The Ramsey model has a much faster convergence speed than the Solow model. Figure 3: Growth simulations when most of the goods are Non-traded Source: Estevadeordal, A. & Taylor, A.M. (2009) Is the Washington Consensus Dead? Growth, Openness, and the Great Liberation, 1970s 2000s, IDB Working Paper Series I38, p

37 The simulations of the Solow and the Ramsey model for this model with non-traded goods are shown in Figure 3. Keeping in mind the assumption that there is no pass through from tariff reductions to the prices of non-traded capital and intermediates, Figure 3 shows smaller impacts from tariff reductions (note the change in the vertical scale of the graphs). Estevadeordal and Taylor (2009) have set the share of traded capital goods to β = 0.3, and the traded share of intermediates to γ = Comparing Figure 3 with Figure 2 shows that the medium growth effects in the non-traded goods case are roughly one-fifth as big as in the fully traded goods case. The long-run output effect in Figure 3 when there is a tariff reduction on capital goods (I) is an increase of 3.7%. A tariff reduction on imported intermediate inputs (X) raises output in the long-run with 5.7% and when both tariffs are eliminated, long-run output rises with approximately 9.5%. The dynamic gains from trade estimated by Estevadeordal and Taylor (2009) arise from tariff reductions on both capital goods and intermediate inputs, and subsequently the biggest share of this effect is felt through the intermediate goods channel. Theory explains that the low estimate suggest a 9.5% increase in output growth after tariff reductions and the high estimate suggest a 56% output growth after the elimination of tariffs. In their view, the growth and level effects should be somewhere in between the low and the high estimate. Although many goods are non-traded, in this paper is shown that more factors play a role when examining the role of intermediate inputs and capital goods on growth, for example learning by doing or the discussion about the elasticity of substitution between inputs. That is why the next step relates the theory to empirics in order to empirically analyze whether reducing tariffs on intermediate inputs promotes growth. The question that is relevant in the research of Estevadeordal and Taylor (2009) is: Does the rate of growth accelerate more in a liberalizing (treatment group) country as compared to non-liberalizing (control group) country? (Estevadeordal and Taylor, 2009, p. 14) To being able to answer this question an empirical design is established based on a panel data set employing 47 importing countries over the period of 1975 to Non-liberalizing countries are the countries that did not or could not lower their tariffs in this period and the liberalizing countries could and actually did lower their tariffs. 37

38 Table 11: Discrete treatment variable; Difference in difference regressions Source: Estevadeordal, A. & Taylor, A.M. (2009) Is the Washington Consensus Dead? Growth, Openness, and the Great Liberation, 1970s 2000s, IDB Working Paper Series I38, p. 42 In Table 11 the results of the most preferred OLS specification are shown. The last column (Column 5) is of main interest. The coefficient of this column shows the difference between countries that did not lower their tariffs and countries that lowered both their capital goods tariffs and their intermediate input tariffs. This coefficient implies a 1 percentage point per year growth acceleration for liberalizing countries, and the result is significant at a 1% level. Note that the OLS specification is robust. These growth accelerations are not due to changes in institutions and schooling, and they cannot be attributed to change in financial openness and macroeconomic policies either. Furthermore, two IV regressions with different instruments are used to cover for endogeneity and the results remain robust. Estevadeordal and Taylor (2009) have analyzed whether the Washington Consensus is dead, focusing on the non-trivial effect of trade liberalization on output growth. There is a strong support for the trade policy descriptions of the WC, including the reduction of tariffs. Theory suggests that lowering tariffs leads to cheaper imports of capital goods and intermediate inputs which subsequently leads to higher output growth. Empirically it has been shown that eliminating the tariffs on capital goods and intermediates spurs growth per year with 1 percentage point. The opposite of reducing tariffs, namely increasing or inducing subsidies, is another way of spurring country s productivity. Horiuchi and Ishikawa (2007) show that a production subsidy 38