- Email: [email protected]
Product standards and export quality: Micro evidence from China
Economics Letters 145 (2016) 274–277
Contents lists available at ScienceDirect
Economics Letters journal homepage: www.elsevier.com/locate/ecolet
Product standards and export quality: Micro evidence from China Cui Hu ∗ , Faqin Lin School of International Trade and Economics, Central University of Finance and Economics (CUFE), 39 South College Road, Haidian District, Beijing, 100081, PR China
highlights • • • • •
This paper studies whether the product standards improve the product quality. China’s transaction level data from customs are used for investigation. We exploit EU’s policy on lighter’s standard as a natural experiment. Triple difference method is adopted for identification. The results reveal that lighter standards lift export quality of China’s lighters to EU.
article
info
Article history: Received 2 March 2016 Received in revised form 28 June 2016 Accepted 30 June 2016 Available online 5 July 2016
abstract Using European Union’s decision on lighters on 11 May 2006 that only lighters which are child-resistant are placed on the market as a natural experiment, this paper firstly examines the impact of product standards on export quality causally. We use China’s HS-8 digit product level trade data and triple difference approach to analyze whether the product standards causally improve the product quality. We get the answer yes. © 2016 Elsevier B.V. All rights reserved.
JEL classification: F12 F15 Keywords: Product standards Export quality Triple difference
1. Introduction Product standards not only affect trade flows, but should also affect product quality directly. They are usually issued by high income countries and such standards are often regarded as some kind of trade barrier by less developed nations. Thus, it is still unclear whether such standards improve or impede export quality. Due to asymmetric information in trade relations, it may decrease the export quality of developing countries. For example, the policy we study in this paper requires that lighters less than 2 Euros must be installed with safety locks, and exporters may satisfy the standard but using inferior materials of other parts to save cost. While there is an increasing number of empirical studies on how product standards affect trade flows (Fontagné et al., 2015; Schuster and Maertens, 2015), the evidence on how product
∗
Corresponding author. E-mail address: [email protected] (C. Hu).
http://dx.doi.org/10.1016/j.econlet.2016.06.034 0165-1765/© 2016 Elsevier B.V. All rights reserved.
standards affect export quality is rather scarce. To the best of our knowledge, this paper offers the first causal empirical evidence on product standards on export quality using China’s micro export data. On 11 May 2006, by Decision 2006/502/EC, the European Commission required that the Member States take measures to ensure that only lighters which are child-resistant are placed on the market (short for ‘‘CR policy’’ thereafter). The decision was in effect on 11 March 2007. Using this policy as a natural experiment, we examine the impact of the product standards on export quality. We employ China customs data during 2004–2008 that covers export transactions of every Chinese exporter for investigation.1 China offers an ideal context to investigate how ‘‘CR policy’’ affects export quality of lighters. On one hand, China is the main importing source of lighters to EU, which accounts for more than 60% of its imports since 2005. On the other, the majority of lighters
1 The data has relevant information, such as trade value, export destination.
C. Hu, F. Lin / Economics Letters 145 (2016) 274–277
275
Table 1 Basic results for the effect of product standards on export quality. Explained variable
(1) Unit value
(2) Unit value
(3) Quality
(4) Quality
EU × Lighter × Transition
0.088 (1.49)
0.056 (0.95)
0.027 (0.23)
−0.084
EU × Lighter × Implement
0.204* (1.92)
0.209** (1.97)
0.698*** (3.26)
0.705** (2.16)
−0.167*** (−19.38)
−0.117*** (−6.72)
−0.033*** (−25.77)
Yes Yes Yes Yes Yes 1 259 403
Yes Yes Yes Yes Yes 1 259 403
Yes Yes Yes Yes Yes 13 025 040
Exchange rate Other interactions Firm fixed effects Product fixed effects Year fixed effects Country fixed effects Observations
Yes Yes Yes Yes Yes 1 259 403
(0.29)
Note: t value in parentheses; Columns (1) and (2) use unit value as the rough measure of quality and other columns use quality measure by Khandelwal et al. (2013). Specifically, column (3) uses estimated quality measure column (4) adds firms not exporting lighter. Other interactions denote EU × Lighter, EU × Transition, EU × Implement, Lighter × Transition and Lighter × Implement. * Significant at 10%. ** Significant at 5%. *** Significant at 1%.
exported by China could not meet the new standards when EU issued the policy. Using unit price as the quality measure as done by Bas and Strauss-Kahn (2015), and the quality measure estimated by the method provided by Khandelwal et al. (2013), we document that product standards lift export quality. 2. Method and results We estimate the ‘‘effective quality’’ for each firm–product– country observation based on the method proposed in Khandelwal et al. (2013). In particular, we estimate the following model, ln xfhct + σ ln pfhct = ϕh + ϕct + ξfcht
(1)
where the subscripts f , h, c and t stand respectively for firm, HS 8-digit product category, destination country and year. x denotes the export quantity, and p is the unit value. ϕh is product fixed effect. ϕct is country–year fixed effect. σ represents the elasticity of substitution. As showed by Khandelwal et al. (2013), with CES utility function accounting for product quality, the estimated log quality equals to qˆ fhct = ξˆfhct / (σ − 1), where ξˆfhct is the residual of Eq. (1) with OLS regression. The intuition behind this approach is that conditional on price, a variety with a higher quantity indicates higher quality. Therefore, the choice of σ is vital for the estimated quality. Instead of picking from existing literature, we use the substitution elasticity estimated with our sample, which reaches a value around 1.45 and falls in the range found by Broda et al. (2006) for China.2 Triple difference method is used to estimate the effect of CR policy on lighter quality. Our triple difference actually relies on three levels of variation. The first is region variation by treating EU as the treatment (EU = 1 and non-EU = 0). The second is the policy treatment by time variation (t = 0 before policy and t = 1 when there is policy). And the third variation is the lighter treatment. The sample we mainly estimate constitutes of firms exporting only lighters and firms exporting both lighters and other goods.3 Lighter treatment means that observations with exporting lighters will be assigned the value 1; otherwise, the value is 0 (Lighter = 1 and non-Lighter = 0). Thus, basically, the estimation
2 The Chinese elasticity of substitution estimated by Broda et al. (2006) is from 1.34 to 108.19. 3 Lighters include products whose HS codes are ‘‘96 131 000’’, ‘‘96 138 000’’, and ‘‘96 139 000’’.
Fig. 1. Flexible estimates of the relationship between product standards and export quality. Note: The solid line is coefficient. The dashed lines represent the 95% confident interval, and the quality is estimated according to method described in the section 2 by Khandelwal et al. (2013). Exchange rate, all other interactions and fixed effects are controlled.
idea of the triple difference can be characterized by an equation as follows: ATTTriple Difference = [(QualityEU,Lighter,t =1 − QualityEU,Lighter,t =0 )
− (QualityEU,NLighter,t =1 − QualityEU,NLighter,t =0 )] − [(QualityNEU,Lighter,t =1 − QualityNEU,Lighter,t =0 )
− (QualityNEU,NLighter,t =1 − QualityNEU,NLighter,t =0 )].
(2)
In order to characterize the triple difference estimator, we run the following regression: qˆ = β EU + × Lighter × Transition
+ γ EU × Lighter × Implement + Z + FEs + ϵ
(3)
where qˆ is the estimated quality; EU × Lighter × Transition (Implement) are interactions of three dummy variables to capture the variance of lighter quality with new standards of EU announced in 2006 and effective in 2007, and Transition equals to year 2006 dummy and Implement equals to after year 2007 dummy. Z includes other control variables such as all the two term interactions (EU × Lighter, EU × Transition, EU × Implement, Lighter × Transition and Lighter × Implement) and the exchange rate which is defined as the Chinese RMB against foreign currency. FEs are the fixed effects including firm, product, country and year. Finally, ϵ is the error term clustered at country–product level. Table 1 reports the main results of our investigation. Columns (1) and (2) use unit value as a rough proxy of quality and other
276
C. Hu, F. Lin / Economics Letters 145 (2016) 274–277
Table 2 Heterogeneous effects of product standards on export quality. Sample
(1) SOEs
(2) PEs
(3) FIEs
(4) Single product firms
(5) Multi-product firms
(6) Large firms
(7) Small firms
EU × Lighter × Transition
−0.161 (−0.25)
−0.058 (−0.18)
0.173 (0.28)
0.160 (0.40)
−0.479 (−1.05)
−1.664 (−1.46)
−0.348 (−1.03)
EU × Lighter × Implement
0.590 (0.96)
0.642** (1.97)
1.760*** (2.69)
1.282*** (3.18)
0.387 (0.84)
2.200* (1.92)
0.416 (1.20)
Exchange rate
−0.467***
−0.302***
−0.802***
−0.913***
−0.463***
−0.972***
−0.386***
Other interactions Firm fixed effects Product fixed effects Year fixed effects Country fixed effects Observations
(−30.29) Yes Yes Yes Yes Yes 731 726
(−11.95) Yes Yes Yes Yes Yes 472 993
(−11.06) Yes Yes Yes Yes Yes 52 583
(−6.75) Yes Yes Yes Yes Yes 21 823
(−32.18) Yes Yes Yes Yes Yes 1 237 580
(−22.07) Yes Yes Yes Yes Yes 4448
(−21.95) Yes Yes Yes Yes Yes 17 375
Note: t value in parentheses; Quality measure is obtained by Khandelwal et al. (2013) method. The largest export share of a variety within a firm exceed 50% is defined as single product firm otherwise the multi-product firm. The export is higher than the median value of the sample is defined as large firms otherwise the small firms. Other interactions denote EU × Lighter, EU × Transition, EU × Implement, Lighter × Transition, and Lighter × Implement. * Significant at 10%. ** Significant at 5%. *** Significant at 1%.
columns exploit quality measure estimated with method described above. While the results in the first three columns are estimated with sample constituting of firms whose exporting goods include lighters, column (4) adds firms not exporting lighters in the control group as a robustness check. We find that the interaction term of EU × Lighter × Implement generates a statistically significant positive coefficient across all columns. Magnitudes of coefficients are slightly higher when using estimated quality than the ones found using the unit value. The difference is attributed to the fact that the estimated quality rules out the change of unit values. However, the estimated coefficients on EU × Lighter × Transition are all insignificant. These results imply that after the implementation of the new standards, quality improves while it does not significantly improve during transition period of the Decision 2006/502/EC.4 This finding is actually consistent to what we observed. For example, with the implementation of the CR policy, Cixi, a county in Zhejiang, developed 5 new brands of qualified lighters and was granted 7 patents in lighter sector in 2007 while there was no patent before then.5 The standard difference-in-difference strategy requires that the trends of export quality will be the same in both lighters exported to Europe and others (including lighters to other countries and all other products) in the absence of Decision 2006/502/EC. As pointed out by Angrist and Pischke (2008), ‘‘The common trends assumption can be investigated using data on multiple periods’’. Following Han et al. (2012), we run flexible estimation of relationship between product standards and export quality, and present the estimated coefficients of the interaction terms between EU dummy and lighter dummy and year dummies and their 95% confidence intervals in Fig. 1. It shows that prior to 2006, there is almost no significant difference in export quality trends between lighters exporting to Europe and other products or lighters exporting to other countries. This assures us the reliability of the triple difference estimation. On top of our baseline results, we do more regressions to see whether there are any heterogeneous effects of such product standards change on export quality across firms in perspective of ownership, product scope and scale. Table 2 reports the results
4 The main results here are robust to choosing other elasticity figures, e.g., from Anderson and van Wincoop (2004). 5 See http://en.wikipedia.org/wiki/Cixi_City and http://baike.baidu.com/view/ 22527.htm?fromId=462450 (in Chinese). Krugman et al. (2012, p.140), also indicate this by writing ‘..... One town produces nearly all of the world’s cigarette lighters......’.
of this exercise. We estimate the elasticity by ownership, product scope and scale and then use the different elasticity to re-estimate the quality measure for each case. First, we look into impacts on firms with different ownerships and the results in columns (1)–(3) indicate that the product standards only significantly affect export quality of non-state owned enterprises, e.g., private firms and foreign-invested firms. The insignificant impact on SOEs might be attributed to their strong political connection with the government and soft budget constraint, which enables them to switch products or markets easily to avoid such shocks. Second, we investigate the effect on single vs. multi-product firms and the results in column (4) and (5) reflect that the product standards only matter for single product firms. This is not hard to understand since multi-product firms can switch products easily facing negative shocks. Finally, we study the impact on single-product firms with different size and the coefficients of the interactions in last two columns tell that large single product firms significantly lift the export quality after the decision. The reason might rely on the fact that large firms can relatively more easily to adapt to the increasing product standards.
3. Concluding remark In this paper, using European Union’s policy change on lighters’ standards as a natural experiment, and China’s product level trade data, we employ triple difference method and new measure of export quality to confirm that product standards will increase export quality.
Acknowledgments We are grateful to Editor Pierre-Daniel Sarte and the anonymous referee for their invaluable comments and tremendous help. Cui Hu acknowledges the financial support from the National Natural Science Foundation of China (71403302). Faqin Lin acknowledges that the work is supported by National Natural Science Foundation of China (71503281) and Major Project Program of the National Social Science Fund of China (12&ZD097&14ZDB120). The work is also supported by program for innovation research in Central University of Finance and Economics, which is highly appreciated by Faqin Lin.
C. Hu, F. Lin / Economics Letters 145 (2016) 274–277
References Anderson, J.E., van Wincoop, E., 2004. Trade costs. J. Econom. Lit. 42 (3), 691–751. Angrist, J.D., Pischke, J.S., 2008. Mostly Harmless Econometrics: An Empiricist’s Companion. Princeton University Press, Princeton. Bas, M., Strauss-Kahn, V., 2015. Input-trade liberalization, export prices and quality upgrading. J. Int. Econ. 95 (2), 250–262. Broda, C., Greenfield, J., Weinstein, D., 2006. From groundnuts to globalization: A structural estimate of trade and growth. NBER Working Papers, 12512. Fontagné, L., Orefice, G., Piermartini, R., Rocha, N., 2015. Product standards and margins of trade: Firm-level evidence. J. Int. Econ. 97 (1), 29–44.
277
Han, J., Liu, R.J., Zhang, J.S., 2012. Globalization and wage inequality: Evidence from urban China. J. Int. Econ. 87 (2), 288–297. Khandelwal, A.K., Schott, P.K., Wei, S.J., 2013. Trade liberalization and embedded institutional reform: Evidence from Chinese exporters. Amer. Econ. Rev. 103 (6), 2169–2195. Krugman, P.R., Obstfeld, M., Melitz, M., 2012. International Economics: Theory & Policy. Addison-Wesley, Pearson, London. Schuster, M., Maertens, M., 2015. The impact of private food standards on developing countries’ export performance: An analysis of asparagus firms in Peru. World Dev. 66 (2), 208–221.
Contents lists available at ScienceDirect
Economics Letters journal homepage: www.elsevier.com/locate/ecolet
Product standards and export quality: Micro evidence from China Cui Hu ∗ , Faqin Lin School of International Trade and Economics, Central University of Finance and Economics (CUFE), 39 South College Road, Haidian District, Beijing, 100081, PR China
highlights • • • • •
This paper studies whether the product standards improve the product quality. China’s transaction level data from customs are used for investigation. We exploit EU’s policy on lighter’s standard as a natural experiment. Triple difference method is adopted for identification. The results reveal that lighter standards lift export quality of China’s lighters to EU.
article
info
Article history: Received 2 March 2016 Received in revised form 28 June 2016 Accepted 30 June 2016 Available online 5 July 2016
abstract Using European Union’s decision on lighters on 11 May 2006 that only lighters which are child-resistant are placed on the market as a natural experiment, this paper firstly examines the impact of product standards on export quality causally. We use China’s HS-8 digit product level trade data and triple difference approach to analyze whether the product standards causally improve the product quality. We get the answer yes. © 2016 Elsevier B.V. All rights reserved.
JEL classification: F12 F15 Keywords: Product standards Export quality Triple difference
1. Introduction Product standards not only affect trade flows, but should also affect product quality directly. They are usually issued by high income countries and such standards are often regarded as some kind of trade barrier by less developed nations. Thus, it is still unclear whether such standards improve or impede export quality. Due to asymmetric information in trade relations, it may decrease the export quality of developing countries. For example, the policy we study in this paper requires that lighters less than 2 Euros must be installed with safety locks, and exporters may satisfy the standard but using inferior materials of other parts to save cost. While there is an increasing number of empirical studies on how product standards affect trade flows (Fontagné et al., 2015; Schuster and Maertens, 2015), the evidence on how product
∗
Corresponding author. E-mail address: [email protected] (C. Hu).
http://dx.doi.org/10.1016/j.econlet.2016.06.034 0165-1765/© 2016 Elsevier B.V. All rights reserved.
standards affect export quality is rather scarce. To the best of our knowledge, this paper offers the first causal empirical evidence on product standards on export quality using China’s micro export data. On 11 May 2006, by Decision 2006/502/EC, the European Commission required that the Member States take measures to ensure that only lighters which are child-resistant are placed on the market (short for ‘‘CR policy’’ thereafter). The decision was in effect on 11 March 2007. Using this policy as a natural experiment, we examine the impact of the product standards on export quality. We employ China customs data during 2004–2008 that covers export transactions of every Chinese exporter for investigation.1 China offers an ideal context to investigate how ‘‘CR policy’’ affects export quality of lighters. On one hand, China is the main importing source of lighters to EU, which accounts for more than 60% of its imports since 2005. On the other, the majority of lighters
1 The data has relevant information, such as trade value, export destination.
C. Hu, F. Lin / Economics Letters 145 (2016) 274–277
275
Table 1 Basic results for the effect of product standards on export quality. Explained variable
(1) Unit value
(2) Unit value
(3) Quality
(4) Quality
EU × Lighter × Transition
0.088 (1.49)
0.056 (0.95)
0.027 (0.23)
−0.084
EU × Lighter × Implement
0.204* (1.92)
0.209** (1.97)
0.698*** (3.26)
0.705** (2.16)
−0.167*** (−19.38)
−0.117*** (−6.72)
−0.033*** (−25.77)
Yes Yes Yes Yes Yes 1 259 403
Yes Yes Yes Yes Yes 1 259 403
Yes Yes Yes Yes Yes 13 025 040
Exchange rate Other interactions Firm fixed effects Product fixed effects Year fixed effects Country fixed effects Observations
Yes Yes Yes Yes Yes 1 259 403
(0.29)
Note: t value in parentheses; Columns (1) and (2) use unit value as the rough measure of quality and other columns use quality measure by Khandelwal et al. (2013). Specifically, column (3) uses estimated quality measure column (4) adds firms not exporting lighter. Other interactions denote EU × Lighter, EU × Transition, EU × Implement, Lighter × Transition and Lighter × Implement. * Significant at 10%. ** Significant at 5%. *** Significant at 1%.
exported by China could not meet the new standards when EU issued the policy. Using unit price as the quality measure as done by Bas and Strauss-Kahn (2015), and the quality measure estimated by the method provided by Khandelwal et al. (2013), we document that product standards lift export quality. 2. Method and results We estimate the ‘‘effective quality’’ for each firm–product– country observation based on the method proposed in Khandelwal et al. (2013). In particular, we estimate the following model, ln xfhct + σ ln pfhct = ϕh + ϕct + ξfcht
(1)
where the subscripts f , h, c and t stand respectively for firm, HS 8-digit product category, destination country and year. x denotes the export quantity, and p is the unit value. ϕh is product fixed effect. ϕct is country–year fixed effect. σ represents the elasticity of substitution. As showed by Khandelwal et al. (2013), with CES utility function accounting for product quality, the estimated log quality equals to qˆ fhct = ξˆfhct / (σ − 1), where ξˆfhct is the residual of Eq. (1) with OLS regression. The intuition behind this approach is that conditional on price, a variety with a higher quantity indicates higher quality. Therefore, the choice of σ is vital for the estimated quality. Instead of picking from existing literature, we use the substitution elasticity estimated with our sample, which reaches a value around 1.45 and falls in the range found by Broda et al. (2006) for China.2 Triple difference method is used to estimate the effect of CR policy on lighter quality. Our triple difference actually relies on three levels of variation. The first is region variation by treating EU as the treatment (EU = 1 and non-EU = 0). The second is the policy treatment by time variation (t = 0 before policy and t = 1 when there is policy). And the third variation is the lighter treatment. The sample we mainly estimate constitutes of firms exporting only lighters and firms exporting both lighters and other goods.3 Lighter treatment means that observations with exporting lighters will be assigned the value 1; otherwise, the value is 0 (Lighter = 1 and non-Lighter = 0). Thus, basically, the estimation
2 The Chinese elasticity of substitution estimated by Broda et al. (2006) is from 1.34 to 108.19. 3 Lighters include products whose HS codes are ‘‘96 131 000’’, ‘‘96 138 000’’, and ‘‘96 139 000’’.
Fig. 1. Flexible estimates of the relationship between product standards and export quality. Note: The solid line is coefficient. The dashed lines represent the 95% confident interval, and the quality is estimated according to method described in the section 2 by Khandelwal et al. (2013). Exchange rate, all other interactions and fixed effects are controlled.
idea of the triple difference can be characterized by an equation as follows: ATTTriple Difference = [(QualityEU,Lighter,t =1 − QualityEU,Lighter,t =0 )
− (QualityEU,NLighter,t =1 − QualityEU,NLighter,t =0 )] − [(QualityNEU,Lighter,t =1 − QualityNEU,Lighter,t =0 )
− (QualityNEU,NLighter,t =1 − QualityNEU,NLighter,t =0 )].
(2)
In order to characterize the triple difference estimator, we run the following regression: qˆ = β EU + × Lighter × Transition
+ γ EU × Lighter × Implement + Z + FEs + ϵ
(3)
where qˆ is the estimated quality; EU × Lighter × Transition (Implement) are interactions of three dummy variables to capture the variance of lighter quality with new standards of EU announced in 2006 and effective in 2007, and Transition equals to year 2006 dummy and Implement equals to after year 2007 dummy. Z includes other control variables such as all the two term interactions (EU × Lighter, EU × Transition, EU × Implement, Lighter × Transition and Lighter × Implement) and the exchange rate which is defined as the Chinese RMB against foreign currency. FEs are the fixed effects including firm, product, country and year. Finally, ϵ is the error term clustered at country–product level. Table 1 reports the main results of our investigation. Columns (1) and (2) use unit value as a rough proxy of quality and other
276
C. Hu, F. Lin / Economics Letters 145 (2016) 274–277
Table 2 Heterogeneous effects of product standards on export quality. Sample
(1) SOEs
(2) PEs
(3) FIEs
(4) Single product firms
(5) Multi-product firms
(6) Large firms
(7) Small firms
EU × Lighter × Transition
−0.161 (−0.25)
−0.058 (−0.18)
0.173 (0.28)
0.160 (0.40)
−0.479 (−1.05)
−1.664 (−1.46)
−0.348 (−1.03)
EU × Lighter × Implement
0.590 (0.96)
0.642** (1.97)
1.760*** (2.69)
1.282*** (3.18)
0.387 (0.84)
2.200* (1.92)
0.416 (1.20)
Exchange rate
−0.467***
−0.302***
−0.802***
−0.913***
−0.463***
−0.972***
−0.386***
Other interactions Firm fixed effects Product fixed effects Year fixed effects Country fixed effects Observations
(−30.29) Yes Yes Yes Yes Yes 731 726
(−11.95) Yes Yes Yes Yes Yes 472 993
(−11.06) Yes Yes Yes Yes Yes 52 583
(−6.75) Yes Yes Yes Yes Yes 21 823
(−32.18) Yes Yes Yes Yes Yes 1 237 580
(−22.07) Yes Yes Yes Yes Yes 4448
(−21.95) Yes Yes Yes Yes Yes 17 375
Note: t value in parentheses; Quality measure is obtained by Khandelwal et al. (2013) method. The largest export share of a variety within a firm exceed 50% is defined as single product firm otherwise the multi-product firm. The export is higher than the median value of the sample is defined as large firms otherwise the small firms. Other interactions denote EU × Lighter, EU × Transition, EU × Implement, Lighter × Transition, and Lighter × Implement. * Significant at 10%. ** Significant at 5%. *** Significant at 1%.
columns exploit quality measure estimated with method described above. While the results in the first three columns are estimated with sample constituting of firms whose exporting goods include lighters, column (4) adds firms not exporting lighters in the control group as a robustness check. We find that the interaction term of EU × Lighter × Implement generates a statistically significant positive coefficient across all columns. Magnitudes of coefficients are slightly higher when using estimated quality than the ones found using the unit value. The difference is attributed to the fact that the estimated quality rules out the change of unit values. However, the estimated coefficients on EU × Lighter × Transition are all insignificant. These results imply that after the implementation of the new standards, quality improves while it does not significantly improve during transition period of the Decision 2006/502/EC.4 This finding is actually consistent to what we observed. For example, with the implementation of the CR policy, Cixi, a county in Zhejiang, developed 5 new brands of qualified lighters and was granted 7 patents in lighter sector in 2007 while there was no patent before then.5 The standard difference-in-difference strategy requires that the trends of export quality will be the same in both lighters exported to Europe and others (including lighters to other countries and all other products) in the absence of Decision 2006/502/EC. As pointed out by Angrist and Pischke (2008), ‘‘The common trends assumption can be investigated using data on multiple periods’’. Following Han et al. (2012), we run flexible estimation of relationship between product standards and export quality, and present the estimated coefficients of the interaction terms between EU dummy and lighter dummy and year dummies and their 95% confidence intervals in Fig. 1. It shows that prior to 2006, there is almost no significant difference in export quality trends between lighters exporting to Europe and other products or lighters exporting to other countries. This assures us the reliability of the triple difference estimation. On top of our baseline results, we do more regressions to see whether there are any heterogeneous effects of such product standards change on export quality across firms in perspective of ownership, product scope and scale. Table 2 reports the results
4 The main results here are robust to choosing other elasticity figures, e.g., from Anderson and van Wincoop (2004). 5 See http://en.wikipedia.org/wiki/Cixi_City and http://baike.baidu.com/view/ 22527.htm?fromId=462450 (in Chinese). Krugman et al. (2012, p.140), also indicate this by writing ‘..... One town produces nearly all of the world’s cigarette lighters......’.
of this exercise. We estimate the elasticity by ownership, product scope and scale and then use the different elasticity to re-estimate the quality measure for each case. First, we look into impacts on firms with different ownerships and the results in columns (1)–(3) indicate that the product standards only significantly affect export quality of non-state owned enterprises, e.g., private firms and foreign-invested firms. The insignificant impact on SOEs might be attributed to their strong political connection with the government and soft budget constraint, which enables them to switch products or markets easily to avoid such shocks. Second, we investigate the effect on single vs. multi-product firms and the results in column (4) and (5) reflect that the product standards only matter for single product firms. This is not hard to understand since multi-product firms can switch products easily facing negative shocks. Finally, we study the impact on single-product firms with different size and the coefficients of the interactions in last two columns tell that large single product firms significantly lift the export quality after the decision. The reason might rely on the fact that large firms can relatively more easily to adapt to the increasing product standards.
3. Concluding remark In this paper, using European Union’s policy change on lighters’ standards as a natural experiment, and China’s product level trade data, we employ triple difference method and new measure of export quality to confirm that product standards will increase export quality.
Acknowledgments We are grateful to Editor Pierre-Daniel Sarte and the anonymous referee for their invaluable comments and tremendous help. Cui Hu acknowledges the financial support from the National Natural Science Foundation of China (71403302). Faqin Lin acknowledges that the work is supported by National Natural Science Foundation of China (71503281) and Major Project Program of the National Social Science Fund of China (12&ZD097&14ZDB120). The work is also supported by program for innovation research in Central University of Finance and Economics, which is highly appreciated by Faqin Lin.
C. Hu, F. Lin / Economics Letters 145 (2016) 274–277
References Anderson, J.E., van Wincoop, E., 2004. Trade costs. J. Econom. Lit. 42 (3), 691–751. Angrist, J.D., Pischke, J.S., 2008. Mostly Harmless Econometrics: An Empiricist’s Companion. Princeton University Press, Princeton. Bas, M., Strauss-Kahn, V., 2015. Input-trade liberalization, export prices and quality upgrading. J. Int. Econ. 95 (2), 250–262. Broda, C., Greenfield, J., Weinstein, D., 2006. From groundnuts to globalization: A structural estimate of trade and growth. NBER Working Papers, 12512. Fontagné, L., Orefice, G., Piermartini, R., Rocha, N., 2015. Product standards and margins of trade: Firm-level evidence. J. Int. Econ. 97 (1), 29–44.
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