Exports and profitability: A note from quantile regression approach

IV. Summary In an attempt to reconcile the ambiguous findings in previous studies of the role of exporting on firms’ profit growth, we argue that the empirical linkage between exporting and profit growth has been clouded by the use of a mean approach. Using an OLS approach, our results do not show a linkage between export participation and the growth of profit estimates. However, quantile treatment effects estimates reveal that export participation has a positive association for those firms with high profit growth at the higher quantiles but a negative link with low profit growth for those firms at the lower quantiles

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This article was downloaded by: [University of Waikato] On: 14 January 2014, At: 18:22 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Applied Economics Letters Publication details, including instructions for authors and subscription information: Exports and profitability: a note from quantile regression approach Huong Vua, Mark Holmesa, Steven Lima & Tuyen Trana a Department of Economics, Waikato University, Hamilton, New Zealand Published online: 14 Jan 2014. To cite this article: Huong Vu, Mark Holmes, Steven Lim & Tuyen Tran (2014) Exports and profitability: a note from quantile regression approach, Applied Economics Letters, 21:6, 442-445, DOI: 10.1080/13504851.2013.866197 To link to this article: PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions Exports and profitability: a note from quantile regression approach Huong Vu*, Mark Holmes, Steven Lim and Tuyen Tran Department of Economics, Waikato University, Hamilton, New Zealand Studies of the linkage between exports and profitability often use mean regres- sion approaches and focus only on European countries. Using a panel data quantile regression approach, this study analyses the linkage between export behaviour and profit growth in Vietnam. Using a panel dataset from 2005 to 2009, our results show an insignificant linkage between export status and firm profit growth when using OLS. However, when using a quantile approach, export participation is found to be positively related to profitability for those firms with high profit growth but negatively related for those firms with low profit growth. This might suggest that the productivity advantages of exporters with low profit growth are absorbed by costs relating to trading activities in overseas markets. Keywords: exports; profitability; quantile approach; SMEs JEL Classification: F14; O12 I. Introduction Since the ground-breaking study of Bernard and Jensen (1995), which described ‘exceptional export perfor- mance’, many empirical studies have shown that the rea- son for exporters having higher productivity than nonexporters stems from a self-selection mechanism rather than learning by exporting (e.g. Wagner, 2007). Such work has led to a further interesting question that has drawn the attention of some recent studies in interna- tional trade. Do exporters with the advantage of higher productivity gain higher profitability, or is this advantage absorbed by extra costs relating to trading activities in overseas markets? The motivation for us to pursue this topic stems from several reasons. First, as noted by Wagner (2011), considering profitability instead of pro- ductivity is very important because profitability reflects the success of firms and the first priority of firms is profit maximization rather than productivity. Second, some stu- dies have found export participation to have a positive impact, but other studies indicate a negative or insignif- icant relationship between firm exporting and profitability (e.g. Lu and Beamish, 2006; Fryges and Wagner, 2010; Grazzi, 2011). Third, all the investigations carried out so far are in the context of European countries (Wagner, 2012). Hence, no generalized inferences can be made. In terms of methodology, existing regression ana- lysis of the relationship between profitability and exports typically relies on OLS or least absolute deviation methods and so only estimate the marginal effects of the covariates on the conditional mean (median) function of profitability. Such estimates sidestep the potentially heterogeneous patterns of the influence of the covariates in the conditional distribution, and this approach provides limited infor- mation about the relationship. Using a quantile regression approach for panel data, this research therefore aims to bring empirical evidence of the role of exporting on profitability in a transitional economy, Vietnam, to fill the gap that exists in the current literature. The quantile approach has further advantages. The results are robust to the existence of outliers (Kizhakethalackal et al., 2013), and they also offer a detailed picture of the relationship. In our *Corresponding author. E-mail: vhv1@waikato.ac.nz Present affiliation for Tuyen Tran: VNU University of Economics and Business, Hanoi, Vietnam. Applied Economics Letters, 2014 Vol. 21, No. 6, 442–445, 442 © 2014 Taylor & Francis D ow nl oa de d by [U niv ers ity of W aik ato ] a t 1 8:2 2 1 4 J an ua ry 20 14 case, we have evidence of a nonlinear relationship between exports and profitability. This has the poten- tial to reconcile the ambiguity in the earlier studies. The remainder of the article is as follows. Section II presents data sources and methodology. Section III dis- cusses the empirical results. The final section summarizes main findings. II. The Data and Methodology The data source The research uses data from the ‘Small and Medium Scale Enterprise Survey in Vietnam’. The surveys were con- ducted in 2005, 2007 and 2009 as collaboration between the Institute of Labour Science and Social Affairs, Vietnam, and Department of Economics of the University of Copenhagen. The original dataset included 2821 enterprises which were interviewed in 2005. The number is 2635 firms in 2007, while a slightly larger number of 2655 were interviewed in 2009.1 The dataset has some inherent advantages. This is a uniquely rich dataset of manufacturing SMEs that covered 10 provinces in 3 regions in Vietnam. It also covers all the major manufacturing sectors namely food processing, wood products and other sectors. Furthermore, the main information on export status of the enterprise and economic indicators as well as firm characteristics is contained in the dataset. Hence, the data enable us to conduct a test of the linkage between export status and profitability.2 Methodology Previous studies often use OLS estimation to consider the role of export status on firm profit growth (e.g. Fryges and Wagner, 2010). However, as Buchinsky (1994) suggests, mean regression techniques have never been satisfactory approaches when considering heterogeneous populations. To consider the potential heterogeneous impacts, we specify the qth quantile (0 < q < 1) of conditional distribution of the dependent variable, given a set of variables Xi, as follows: Qqðyit=xitÞ ¼ aq þ xitβq þ uitαq (1) where yit is the profit growth of firm i through time and uit represents for unobservable factors such as products quality and management quality. Avector of independent variables (xit) is included. First, the main interest variable, export participation, is captured by a dummy variable to minimize measurement errors. We also con- sider other types of exporting activities. Continuous exporters are firms that export through the study period, whereas starting exporters are enterprises that do not export in year t – 1 but export in year t. Exporting stoppers are firms that export in year t – 1 but do not export in year t.3 Second, firms’ profitability may be determined by standard firm characters such as firm size, firm age and innovation (e.g. Grazzi, 2011).4 In addition, the behaviour of SMEs may be different among various sectors, kinds of ownership and locations in Vietnam (Rand and Torm, 2011; Vu et al., 2013). We control for all these by using a dummy for low technol- ogy sectors, a dummy for household ownership and an urban dummy. Cameron and Trivedi (2009) show that estimation of Equation 1 based on the qth quantile regression involves minimizing the absolute value of the residual using the following objective function: QðβqÞ ¼ min β Xn i¼1 yit  xitβq  h i ¼ min  X i:yitxiβ qjyit  xitβqj þ X i:yit <xitβ ð1 qÞjyit  xitβqj  (2) A series of studies have discussed the problem of captur- ing unobserved factors through a fixed effects quantile model (e.g. Koenker, 2004; Canay, 2011). We also follow these approaches. According to Canay (2011), the estima- tion procedure comprises two stages. In the first stage, the conditional mean of uit is estimated. In the second stage, this component is subtracted from the original dependent variable, and then the standard estimation of quantile regression is used. III. Empirical Results Column 1 in Table 1 reports results based on the average regression approaches. There is a statistically insignificant difference in profit growth between exporters and nonexporters, a finding consistent with previous studies (e.g. Wagner, 2011). Similar results in the linkage with profit growth have also been found when using export participation at 1 This data has been kindly shared by Prof. John Rand. 2Variables with current prices are deflated to 1994 prices using GDP deflators to avoid biases that might arise from inflation. 3 The direct information of import status is not available. Export intensity is also unavailable in 2007. The caveats of data prevent us from considering these covariates in the regression. 4We also use firm size squared and firm age squared to capture the nonlinear nature of the linkages. Exports and profitability 443 D ow nl oa de d by [U niv ers ity of W aik ato ] a t 1 8:2 2 1 4 J an ua ry 20 14 different stages. Fixed effect estimations do not pro- vide qualitatively different results.5 A totally different picture emerges when using quantile regression. As displayed by the top half of Table 1 and the top left graph in Fig. 1, there is a positive relationship between export participation and profit growth at the 70th and 80th percentiles, but a negative linkage is observed between export participation with enterprises having low profit growth at the 10th percentile. These results imply that the average approach has clouded the role of export activities in firm profit growth at different points. The findings here suggest that the productivity advantages of exporters compared with nonexporters are found for firms having high profit growth at 70th and 80th percentiles. For firms with low profit growth at 10th percentile, these advantages are possibly absorbed by costs relating to trading activities on overseas markets such as entry costs and advertisement costs. Our results hence move towards reconciling the mixed findings of previous results in the literature (See Wagner (2012) for a review). If export participation is replaced by each exporting activity in turn, then the lower half of Table 1 reports an insignificant linkage between exporting stoppers and firm profit growth. However, the negative and significant links between firms having low profit growth at the lower quantiles are still being observed in the case of both continuous and starting exporters. This is further demon- strated using the confidence intervals shown in Fig. 1. Regarding firm characteristics, our findings in Table 1 are generally consistent with other international empirical studies. For example, we find that a higher profit growth is associated with firms of a larger size. In addition, while innovators gain a higher profit growth than noninnova- tors, firms with more business experience have a lower growth in profitability compared to firms with less busi- ness experience. IV. Summary In an attempt to reconcile the ambiguous findings in previous studies of the role of exporting on firms’ profit growth, we argue that the empirical linkage between exporting and profit growth has been clouded by the use of a mean approach. Using an OLS approach, our results do not show a linkage between export participation and the growth of profit estimates. However, quantile treatment effects estimates reveal that export Table 1. Exports and profit growth Variables OLS Fixed effect quantile regression q10 q20 q30 q40 q50 q60 q70 q80 q90 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) Export participation and profit growthI Export −0.02 −0.09*** −0.04 −0.02 −0.02 −0.01 0.02 0.05* 0.09* 0.06 (0.035) (0.050) (0.030) (0.015) (0.017) (0.019) (0.021) (0.024) (0.034) (0.037) Size in log 0.02* −0.01 0.01*** 0.02** 0.02** 0.02** 0.02** 0.03** 0.04** 0.05** (0.008) (0.009) (0.006) (0.004) (0.003) (0.003) (0.004) (0.004) (0.005) (0.010) Firm age −0.01** −0.01** −0.01** −0.01** −0.01** −0.01** −0.01** −0.01** −0.01** −0.01** (0.002) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.002) Innovation dummy 0.03* 0.02 −0.00 0.00 0.00 0.01*** 0.02* 0.02** 0.02** 0.03* (0.011) (0.012) (0.008) (0.007) (0.005) (0.005) (0.006) (0.006) (0.008) (0.014) Constant 0.13** −0.19** −0.08** −0.03* 0.01 0.04** 0.09** 0.14** 0.23** 0.43** (0.032) (0.029) (0.019) (0.015) (0.013) (0.011) (0.013) (0.013) (0.022) (0.036) Other exporting activities and profit growtha Continuous exporters −0.06 −0.16 −0.13*** −0.07*** −0.07*** −0.01 0.01 0.02 0.07 −0.01 (0.062) (0.101) (0.076) (0.039) (0.044) (0.051) (0.052) (0.067) (0.079) (0.116) Starting exporters −0.04 −0.03 −0.04 −0.05*** −0.06*** −0.04*** −0.04 0.01 0.00 −0.06 (0.046) (0.069) (0.034) (0.027) (0.033) (0.026) (0.044) (0.049) (0.051) (0.074) Exporting stoppers −0.11 −0.17 −0.06 −0.05 −0.02 −0.03 −0.03 0.04 0.02 0.00 (0.071) (0.112) (0.092) (0.042) (0.036) (0.029) (0.051) (0.056) (0.056) (0.075) Notes: Bootstrap SEs in parentheses with 2000 replications. *** significant at 10%, * at 5% and ** at 1%. OLS SEs are robust. Model I controls for firm size squared, firm age squared, year 2009, urban dummy, a dummy for household ownership and a dummy for low technology sectors. The number of observations is 7612. aThis model also controls for other independent variables as Model I. 5 The results are available on request. 444 H. Vu et al. D ow nl oa de d by [U niv ers ity of W aik ato ] a t 1 8:2 2 1 4 J an ua ry 20 14 participation has a positive association for those firms with high profit growth at the higher quantiles but a negative link with low profit growth for those firms at the lower quantiles. Acknowledgement The author Huong Vu is grateful for the helpful feedback from Prof. Canay regarding this article. Funding The author Huong Vu gratefully acknowledges financial support from the Vietnamese government. References Bernard, A. B. and Jensen, J. B. (1995) Exporters, jobs, and wages in US manufacturing: 1976–1987, Brookings Papers on Economic Activity, Microeconomics, 1995, 67–119. Buchinsky, M. (1994) Changes in the US wage structure 1963– 1987: application of quantile regression, Econometrica: Journal of the Econometric Society, 62, 405–58. Cameron, A. C. and Trivedi, P. K. (2009) Microeconometrics Using Stata, Vol. 5, Stata Press, College Station, TX. Canay, I. A. (2011) A simple approach to quantile regression for panel data, The Econometrics Journal, 14, 368–86. Fryges, H. and Wagner, J. (2010) Exports and profitability: first evidence for German manufacturing firms, The World Economy, 33, 399–423. Grazzi, M. (2011) Export and firm performance: evidence on productivity and profitability of Italian companies, Journal of Industry, Competition and Trade, 12, 413–44. Kizhakethalackal, E. T., Mukherjee, D. and Alvi, E. (2013) Quantile regression analysis of health-aid and infant mor- tality: a note, Applied Economics Letters, 20, 1197–201. Koenker, R. (2004) Quantile regression for longitudinal data, Journal of Multivariate Analysis, 91, 74–89. Lu, J. W. and Beamish, P. W. (2006) SME internationalization and performance: growth vs. profitability, Journal of International Entrepreneurship, 4, 27–48. Rand, J. and Torm, N. (2011) The benefits of formalization: evidence from Vietnamese manufacturing SMEs, World Development, 40, 983–98. Vu, H., Lim, S., Holmes, M. et al. (2013) Firm exporting and employee benefits: first evidence from Vietnam Manufacturing SMEs, Economics Bulletin, 33, 519–35. Wagner, J. (2007) Exports and productivity: a survey of the evidence from firm‐level data, The World Economy, 30, 60–82. Wagner, J. (2011) Exports, imports and profitability: first evi- dence for manufacturing enterprises, Open Economies Review, 23, 747–65. Wagner, J. (2012) International trade and firm performance: a survey of empirical studies since 2006, Review of World Economics, 148, 235–67. –0 .2 0 –0 .1 0 0. 00 0. 10 0. 20 P ro fit g ro w th im pa ct 0 0.2 0.4 0.6 0.8 1 Quantile Quantile impact 90% upper CI Export participation and profit growth –0 .3 0 –0 .2 0 –0 .1 0 0. 00 0. 10 0. 20 P ro fit g ro w th im pa ct 0 0.2 0.4 0.6 0.8 1 Continuous exporters and profit growth –0 .2 0 –0 .1 0 0. 00 0. 10 P ro fit g ro w th im pa ct 0 0.2 0.4 0.6 0.8 1 Starting exporters and profit growth –0 .3 0 –0 .2 0 –0 .1 0 0. 00 0. 10 0. 20 P ro fit g ro w th im pa ct 0 0.2 0.4 0.6 0.8 1 Exporting stoppers and profit growth 90% lower CI OLS impact Quantile Quantile impact 90% upper CI 90% lower CI OLS impact Quantile Quantile impact 90% upper CI 90% lower CI OLS impact Quantile Quantile impact 90% upper CI 90% lower CI OLS impact Fig. 1. Slope and 90% coefficient intervals for quantile treatment regression Exports and profitability 445 D ow nl oa de d by [U niv ers ity of W aik ato ] a t 1 8:2 2 1 4 J an ua ry 20 14

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