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Impact of Exchange Rate and Firm Heterogeneity on Exports: Empirical Evidence from Four ASEAN Economies.

1. Introduction

Ever since China's labour costs have started escalating and the country's growth began slowing down, ASEAN has come under the global spotlight. The Association, composed of ten countries, (1) has a combined population of 650 million, making it the fourth most populous economy, while its nominal GDP stands at US$2.8 trillion, placing it sixth in the list of largest economies. In terms of international trade, it is the fourth largest exporting region--after the European Union, North America, and China/Hong Kong. The grouping plays a central role in Asian economic regional integration initiatives and its member economies are part of major regional free trade agreements such as the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP), Regional Comprehensive Economic Partnership (RCEP), ASEAN+1, inter alia.

As ASEAN leaders seek to replicate China's economic growth miracle through export-driven expansion, the exchange rate, which measures the relative price competitiveness of a country's exports, has emerged as an extremely important factor. In fact, devaluation of the Chinese RMB is generally believed to be a key reason for the success of the country's exports (Ahmed 2009; Aziz and Li 2007; Cheung, Chinn and Fujii 2009). The Chinese evidence is consistent with the conventional view that depreciation or devaluation of a local currency will lead to more exports by making domestic goods more competitive in the international market. Not only in China, but the quick recovery seen in Europe and Japan following the Second World War, too, was largely attributed to the devaluation of their currencies (Eichengreen 2005, 2006). Moreover, currency deprecation has been found to have hastened the economic recovery process during the Great Depression of the 1930s (Eichengreen and Sachs 1985). In a nutshell, there is enough evidence to show that exchange rate devaluation is a useful tool to boost exports.

Interestingly, in recent years, many ASEAN countries seem to defy this trend, as their total volume of exports has increased despite a steady appreciation of the real effective exchange rate (REER). As shown in Figure 1, between 2005 and 2015, five ASEAN countries (Indonesia, the Philippines, Vietnam, Laos and Cambodia) saw an upward trend in their respective REERs, which indicates that the exports from these economies were losing their price competitiveness (or were witnessing an increase in export prices) ceteris paribus at a certain level of exchange rate pass-through, but their aggregated exports were expanding almost throughout this period. With the exception of Indonesia, which saw some fluctuations, this is seen in all the other countries.

This distortion in the trade and exchange rate nexus observed in these countries using aggregated data can have important implications for policymakers and researchers in the region and beyond. The observation suggests that the established link between trade and exchange rates may not hold true any longer, at least not in the rising ASEAN region. In other words, the devaluation or depreciation of a local currency cannot be seen either as a policy tool or a windfall for economies that bet on an export-based strategy for economic development.

Therefore, it is meaningful and timely to ask whether, at a micro-level, the export performance of ASEAN firms is immune to the impact of exchange rate appreciation. And, if that is not the case, what type of firms are more sensitive to exchange rate movements? At the point of writing, no published studies have been found to address this particular phenomenon, especially using firm-level data.

In order to fill the gap, this paper uses firm-level panel data from four ASEAN countries (Indonesia, Vietnam, the Philippines and Laos), as collected by the World Bank's IFC Enterprise Survey for selective years between 2009 and 2016. Due to the "zero trade" problem in the dataset, the Poisson-pseudomaximum likelihood (PPML) approach is employed as the main estimation method. Supplementary empirical analysis techniques, including Tobit, ad hoc solution and Heckman's two-stage model are also used in this study.

For the baseline econometric analysis, change in a firm's real exports is assumed to be a function of the real effective exchange rate level and its volatility and firm characteristics (firm size and labour productivity), while controlling for unobserved time-invariant effects of year, country and sector. Next, the equation is extended by including other firm heterogeneities as explanatory variables, including foreign ownership, internationally recognized quality certification, and financial obstacles. Alternative exchange rate measurement tools--nominal effective exchange rate (NEER) and US dollar-local currency exchange rate--and data decomposition are employed for robustness checks. Finally, the interaction terms--exchange rate and firm heterogeneities (SMEs, prior export experience, foreign and domestic affiliation, foreign content in exports)--are constructed to analyse how firms with different characteristics respond to exchange rate appreciation.

The findings of this study suggest that, first, contrary to conventional wisdom, exchange rate appreciation actually discourages exports of ASEAN-based companies. Second, firms' responses to currency appreciation vary; while SMEs and first time exporters are more fragile when it comes to exchange rate movements, exporters can reduce such risks through foreign or domestic affiliations (although foreign ownership proves to be more helpful). Third, firms whose exports consist of foreign inputs are less affected by the rise in the value of local currency. And fourth, firms in the services sector are more sensitive to currency appreciation than those in manufacturing.

In addition to the studies mentioned above, the results of this paper are also related to literature on: firm heterogeneity in export decision (Melitz 2013; Bernard and Jensen 1999 and 2004); exchange rate, sunk cost, and hysteresis in trade (Baldwin and Krugman 1989; Dixit 1989; Campa 2004); and the connection between exchange rate and trade (Leigh et al. 2015; Amiti, Itskhoki, and Konings 2014; Bernini and Tomasi 2015).

This paper is structured as follows. The next section covers a brief overview of the existing literature, while the third section focuses on the data used in the study. The fourth section includes the empirical framework and methodology. The empirical results are presented in the subsequent section. Limitations of the research are acknowledged in the sixth section, and the final section concludes.

2. Literature Review

Real exchange rate movements affect exports through two channels: first, via the level/magnitude of the real exchange rate; and second, via real exchange rate volatility. The former is an important component of relative price for firm exports, while the latter is a vital element of the fixed costs incurred by firms to participate in international trade. Although there are many studies on the impact of exchange rate on exports, the vast majority of them do not--theoretically or empirically--conclude whether or not the level of real exchange rate and real exchange rate volatility increase exports. Given this background, this section reviews some of the existing studies on the effect of real exchange rate depreciation and exchange rate volatility on exports.

In theory, real exchange rate depreciation is said to lower export prices and raise import prices (Krugman 1999; Kandil and Mirzaie 2002; Greenaway, Kneller, and Zhang 2010). Therefore, the effect of exchange rate depreciation on exports depends on this offset effect. A large number of recent empirical studies also show that real exchange rate depreciation increases exports (Bahmani-Oskooee and Kara 2003; Hausmann, Pritchett, and Rodrik 2005; Ng et al. 2008; Freund and Pierola 2012). In literature devoted to the Asian region, too, many studies find that real exchange rate depreciation increases exports. Fang, Lai, and Miller (2006), for example, find that real exchange rate depreciation has a significant, positive effect on export growth of seven Asian countries (Indonesia, Japan, Korea, Malaysia, the Philippines, Taiwan and Thailand), but not Singapore. Jongwanich (2009), who analysed eight countries (China, Hong Kong, India, Indonesia, Korea, Malaysia, Singapore and Thailand), also notes that real exchange rate depreciation generates a higher volume of exports. Mirroring the opposite trend of increase in exports on account of real exchange rate depreciation, many studies also document the negative effect of real exchange rate appreciation on exports (Bugamelli and Infante 2003; Campa 2004; Das, Roberts, and Tybout 2007; Greenaway, Kneller, and Zhang 2008; Thorbecke and Smith 2010). In contrast, Abeysinghe and Yeok (1998) and Wilson and Tat (2001) argue that real exchange rate appreciation does not reduce the volume of exports in some Asian countries. Likewise, Bernard and Jensen (2004) analysed US exports and Wilson (2001) studied the export markets of Singapore, Malaysia and Korea, and both studies report that real exchange rate does not have a significant impact on bilateral trade.

A large number of studies also investigate the effect of real exchange rate volatility on exports. The traditionally accepted view is that exchange rate volatility is negatively associated with trade flows, given the idea of uncertainty (Ethier 1973; Arize 1997). In fact, in the "new" new trade theory (NNTT) developed by Melitz (2003), exchange rate volatility serves as a fixed cost for exporting firms. Specifically, higher fixed costs from high exchange rate volatility negatively affect firm exports.

However, Broil and Eckwert (1999) highlight the theoretical possibility of a positive relationship between exchange rate volatility and exports, as higher exchange rate volatility may also increase the real option to export to the world market. In addition, De Grauwe (1988) also suggests that, in the event of large exchange rate fluctuations, firms can increase the volume of exports to offset the potential loss of revenues. Empirical evidence on the impact of exchange rate related risks on exports is mixed, but most recent studies underline the negative effects (Arize, Osang, and Slottje 2000; Rose 2000; Arize, Malindretos and Kasibhatla 2003; Freund and Pierola 2012). Papers that focus on Asian economies also find that the relationship is overwhelmingly negative. For example, Fang, Lai, and Miller (2006) establish the negative effects for Japan, Singapore and Taiwan. Similarly, Fang, Lai, and Thompson (2007) show that exchange rate risks have a detrimental impact on export revenues for Japan and seven developing Asian countries: Indonesia, Korea, Malaysia, the Philippines, Singapore, Taiwan and Thailand. Chit, Rizov, and Willenbockel (2010) report negative effects of exchange rate volatility on real exports for five emerging countries: China, Indonesia, Malaysia, the Philippines and Thailand. On the contrary, studies that analysed developed countries such as Japan, the US, Germany and France find positive effects (Asseery and Peel 1991; Kroner and Lastrapes 1993; McKenzie and Brooks 1997). Hall et al. (2010), who focused on ten emerging market economies and eleven other developing countries, also support these results. Specifically, their paper finds that exchange rate volatility negatively affects exports of developing countries, but has no impact on exports of emerging market economies.

To sum up, in extant literature, there are a number of studies that underscore the positive effects of real exchange rate depreciation and negative effects of real exchange rate volatility on exports, but they are neither theoretically nor empirically conclusive. In addition, most of these studies use aggregated country-level figures due to data limitation. Therefore, this paper attempts to fill these gaps in literature and investigates the effect of real exchange rate movements on exports in Southeast Asia at the firm level.

3. Data

Two data points are employed in this study: exchange rate and firm-level trade in four (2) ASEAN countries. To measure each country's exchange rate, we use the annual consumer price index (CPI) based REER for 178 countries, along with the Euro Area database developed by Bruegel, a think-tank in Brussels. The real and nominal effective exchange rates are calculated to measure the real value of a country's currency against a basket of its trading partners, and the base year is 2007. The dataset (3) has two subsets: the broad index considers 172 trading partners and is available from 1995 onwards; while the narrow index considers sixty-seven trading partners and is available from 1960 onwards. We rely on the monthly CPI REER figures for 165 countries and the Bruegel database to calculate exchange rate volatility. Although the World Bank, the Organization for Economic Co-operation and Development (OECD) and the Bank of International Settlement (BIS) all publish effective exchange rate data, Bruegel's database is the most comprehensive set that covers the four ASEAN countries that fall within the scope of this study. An increase in REER and NEER indicates the appreciation of location currency. And, the local currency to US dollar ratio used for robustness check is collected from the International Monetary Fund (IMF) website.

The firm-level export data is extracted from the World Bank's IFC Enterprise Survey database. Every year, the World Bank and its private contractors use stratified random sampling to conduct several firm-level surveys in selected countries. The database is compiled based on the survey results of numerous face-toface interviews with business owners, top bosses and department manager mainly in the manufacturing and services sectors. Although many questions may overlap, the surveys are structured in the form of two separate questionnaires for manufacturing and services. The GDP deflator published by the World Bank is then used to calculate firms' real exports.

As the study uses firm-level unbalanced panel data for Indonesia, Vietnam, the Philippines and Laos in selected years between 2009 and 2016, there are 5,032 observations, after dropping missing values in key explanatory variables as shown in Table 1.

Although the World Bank survey does not include unit price and quantity of each firm's main products, it reveals crucial information on firm characteristics and export behaviour. Based on the dataset, we can calculate a firm's extensive and intensive exports using export participation ratio and export volume, respectively, and obtain information on firm heterogeneity--such as firm size; labour productivity; whether the firm has any foreign affiliation, or internationally recognized quality certificates; and ease of access to finance.

As reported in Table 2, the descriptive statistics show that, on average, exporting firms: employ a large number of employees; are more productive; are more likely to be affiliated with foreign owners; have several internationally recognized quality certificates; and face few financial obstacles. (4) In addition, only a small proportion (24.2 per cent) of companies actually engage in exports, which is consistent with existing literature.

As can be seen from Tables 3, 4 and 5, export participation rate (5) varies significantly across time periods, countries and sectors, which hints at the importance of unobserved factors in firms' export decision. Theoretically and conceptually, some of these factors that can lead to heterogeneity in firm exports include: different economic development strategies; specific export promotion policies; home country's geographic location; intrinsic industry characteristics; and relevant historical events such as the Global Financial Crisis. For instance, 27.7 per cent of the total number of firms participated in global exports in 2009, (6) but this figure dropped to 13.6 per cent in 2016. In the survey, almost a third of Vietnamese firms have benefited from the natural endowment of a 3,260-kilometre-long coastline, while 83 per cent of companies in Laos--a land-locked nation--do not have any sales from abroad. The same variation is observed at the sectoral level, as presented in Table 5.

4. Empirical Framework and Methodology

Based on the seminal studies on firm heterogeneity and export behaviour by Melitz (2013) and Bernard and Jensen (1999 and 2004), we include variables related to exchange rate movements, exchange rate level and exchange rate volatility in our model. The model specification is as follows:

[mathematical expression not reproducible]

where i, t, s, c, stand for firm i, survey year (7) t, industry (8) s and country c, respectively. The dependent variable Y denotes the real exports (9) of a firm i, in year t, industry s and country c. REER--the primary variable of interest--and ER Volatility represent the real effective exchange rate and its volatility in year t. Here, exchange rate volatility (10) is measured as the standard deviation of the first difference of logarithm of monthly exchange rate in current year t. X is the matrix of vectors of firm characteristics used in previous studies--firm size and firm productivity (measured by labour productivity rather than total factor productivity (TFP)" due to data limitations). Additionally, firm heterogeneity also includes dummy variables of foreign ownership and internationally recognized quality certificate, (12) as well as self-reported obstacles in accessing finance. (13) As mentioned above, because of the unobserved factors that affect firms' export performance, we also control for the fixed effects of time, country and sector. While the lagged dependent variable is also controlled for (due to the dynamic nature of exports), past studies suggest that lagged real exports have no statistically significant effect on firms' current export performance. The low data frequency (a six-year gap between two time periods, except for Laos) is believed to have an effect on the econometric results. The description of dependent and independent variables is provided in Table 6.

A challenge often encountered while studying firms' export behaviour is that many companies actually do not export--the so called "zero trade" problem. As presented in Table 7, 3,813 out of 5,032 companies (75.8 per cent) report no overseas sales, which indicates a serious case of the zero trade problem. Ignoring the problem will lead to biased estimation results, while deleting all zero values of the dependent variable will result in significant loss of information hidden in these values.

In empirical literature, although there is no consensus on the most effective way of eliminating the zero trade issue, a few methods are often used to address the problem. These are: the Tobit (14) model; the ad hoc solution; (15) the Heckman (16) two-step sample selection model; the NB (17) (negative binomial) model; and the PPML (18) (Poisson pseudo maximum likelihood) approach. The advantages and disadvantages of each model are as explained in the notes.

In this study, PPML is employed as the main estimation method, primarily because it is the most popular tool to tackle this problem. However, additional confirmatory analysis using the alternative methods is also conducted, as suggested by Herrera (2013) and Kareem, Martinez-Zarzoso, and Brummer (2016).

5. Estimation Results

The baseline results using pooled ordinary least squares (OLS), Tobit, ad hoc solution, Heckman's sample selection model, NB model and PPML (19) are presented in Table 8. Despite the difference in estimation methods, (20) overall, the results are consistent and expected. The coefficient of REER is negative and statistically significant in all estimations except the Heckman sample selection model, where the sign is negative but the coefficient is not significant. Even though the OLS, Tobit and ad hoc solution report a good result, caution is needed when interpreting the figures. The much lower number of observations while using OLS as compared to the other methods (967 versus 4,232) raises a red flag in terms of significant loss of information and estimation bias. Also, the magnitude of the coefficient in the Tobit model is suspicious--an increase of REER by one point will lower firms' real exports by 257 per cent. The ad hoc solution displays an economically reasonable and statistically significant coefficient with the right sign, yet the method lacks theoretical backing and generates a biased result. The NB regression is then used to check for any over-dispersion in the PPML; and the result shows that the Poisson distribution assumption is appropriate. Based on the PPML estimation method, which is the least biased and most appropriate to deal with heterogeneity, a one point increase in REER (currency appreciation) lowers a firm's real exports by 4.2 per cent, on average. Consistent with literature, all other explanatory variables report statistically significant results. While exchange rate volatility discourages firm exports, firm size and labour productivity (21) are associated with higher export volumes.

Table 9 reports the results of extending the baseline analysis to include more firm-specific variables, including foreign ownership, internationally recognized quality certificate and obstacles pertaining to access to finance. It is not surprising that the REER and exchange rate volatility coefficients get smaller but remain statistically significant and retain their negative signs as more explanatory variables are controlled for. As expected, both foreign ownership and internationally recognized quality certificate are positively associated with real exports at the firm level, whereas financial obstacles hinder such exports (low readings indicate fewer constraints in accessing finance).

To verify the robustness of the estimation results, we run three regressions and the results successfully pass the sensitivity test. First, the REER is replaced with two alternative measures of exchange rate--the NEER and the US dollar; (22) the results are shown in Tables 10 and 11. Next, we decompose the dataset into manufacturing and services, details of which are provided in Table 12. All results are as expected and consistent with literature. An interesting finding is that the services sector is more sensitive to exchange rate appreciation and volatility. Smith (2004) and Eichengreen and Gupta (2012) also found service exports be more exchange rate sensitive than the exports of other sectors. Since the sector uses fewer imported foreign inputs compared to manufacturing, the heightened sensitivity can be attributed to the small offset effect between foreign inputs and exports.

Interaction terms are also introduced to examine firm heterogeneity in response to local currency fluctuations. Specifically, we are interested in finding out whether small and medium-sized enterprises (SMEs) (23) and firms with prior export experience are more sensitive to movements in and stability of the exchange rate. We also want to investigate whether having a foreign and/or conglomerate (24) affiliation through ownership affects firms' export performance, and if foreign contents (25) or imports lower firms'

There are several interesting findings. First, Table 13 suggests that SMEs, which have fewer economic resources, are more sensitive to exchange rate appreciation (and volatility in general). Second, real exports of firms with prior export experience are more stable compared to first time exporters, when local currency becomes less competitive and fluctuates considerably, as shown in Table 14. This is most likely due to the sunk cost of trade, and presents another example of trade hysteresis (Baldwin and Krugman 1989; Dixit 1989). Third, it should be noted that both foreign as well as conglomerate affiliations help mitigate firms' exchange rate risks, as indicated in Tables 15 and 16. Apart from signalling the advantages inherited from the domestic parent company, the findings also imply that firms with foreign affiliations are more likely to increase their exports even during a state of currency appreciation, at least in the case of the four ASEAN countries. These companies can further absorb shocks generated by exchange rate movements by adjusting of intra-firm transactions. Finally, from Table 17, it can be seen that firms with imported or foreign inputs are less responsive to exchange rate appreciation and volatility. This reconfirms the conceptual framework and theoretical literature that global production networks have lowered the effects of exchange rate movements on trade, as companies with higher foreign imports have a lower exchange rate pass-through and exchange rate and trade link (Amiti, Itskhoki, and Konings 2014). Ando and Iriyama (2009) and Jongwanich (2010) have also shown that export products related to global production networks tend to be less affected by exchange rate movements.

6. Limitations

The paper has some limitations, mostly related to the difficulty in finding data. First is the potential endogeneity problem. As documented in literature on exports and firm growth, a reverse causality can exist between firm size, productivity and volume of exports. This is also true for financial obstacles. We were unable to find a perfect instrument to resolve this issue. (26) Additionally, it was not feasible to control the unobserved time-invariant variable hidden in the error term, owing to a low frequency and the relatively short time duration of the panel data. Another shortcoming is the lack of sufficient data to construct firm-specific REER. Although REER has some degree of signalling impact, and is generally considered a proxy of a country's export competitiveness, using effective exchange rate to examine firms' export performance comes with the unrealistic assumption that all firms have the same export structure and weights of export destinations as the nation as a whole. This can hardly be true, especially for SMEs that usually trade with a limited number of countries. Also, data limitations while calculating exchange rate pass-through and export price elasticity make it difficult to understand how exchange rate movements affect firms' pricing and export decisions.

7. Conclusion

This study shows that the commonly accepted macro-picture of ASEAN countries being totally immune to currency appreciation is incorrect. Using firm-level data from four ASEAN economies for selected years between 2009 and 2016, we arrive at four important findings. First, local currency appreciation discourages firm exports at the micro-level. Second, firms' responses to exchange rate appreciation are heterogeneous, and are contingent on several company-specific characteristics. For example, SMEs and first-time exporters are more sensitive to exchange rate movements. Likewise, both foreign and domestic affiliations help firms alleviate the exchange rate risk; but, foreign ownership, which brings capital but also opportunities to join international network and technical know-how, proves more helpful than having a domestic shareholder. Third, firms with foreign imports are less affected by the rise of local currency value, as the gains from imports offset the losses incurred via exports. This provides a solid foundation to explain why widespread global production networks weaken the link between exchange rate and trade. In fact, governments should develop SME support policies and encourage foreign investments to promote greater participation of local firms in global production networks. Finally, firms in the services sector are more sensitive to currency appreciation than those in manufacturing, most likely due to a higher exchange rate pass-through.

Despite certain limitations, this empirical exercise suggests that policymakers and researchers should be cautious when interpreting the relationship between exchange rate movement and export performance solely based on common perceptions or aggregated data.

NOTES

(1.) The ten ASEAN countries are Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand and Vietnam.

(2.) The four ASEAN countries are Indonesia, the Philippines, Vietnam and Laos. The main reason behind the decision to choose these four particular countries is data (un)availability.

(3.) The data can be downloaded from: http://bruegel.org/publications/datasets/real-effective-exchange-rates-for-178-countries-a-new-database/

(4.) The explanatory variable of financial obstacles has fewer observations because the negative and non-applicable values are excluded.

(5.) Export participation rate is calculated as the number of exporters over the total number of firms. It can be divided by year, country and sector.

(6.) It appears that the negative impact of the 2008 Global Financial Crisis has had a lagged effect on firms' exit from export markets.

(7.) Surveys were conducted a year after the interviews. For example, the 2015 survey data is collected based on the survey results of 2014.

(8.) Industry refers to the establishment's actual industry classification, based on the main activity at the time of the survey.

(9.) Export value is the sum of indirect and direct overseas sales. GDP deflator is used to obtain the real value.

(10.) In literature, there is no consensus on the precise measurement of exchange rate volatility and the time horizon. However, the standard deviation of the first difference of logarithm of monthly exchange rate method over a time horizon is the most widely used approach to measure exchange rate volatility (Clark et al. 2004). The authors are interested in the short-term volatility, so time range of the current year T is chosen for analysis. The exchange rate volatility over current year T and previous year T-1 are also used to perform the analysis and the results are the same.

(11.) Ideally, TFP should be used to measure firm's productivity. The authors have tried to calculate TFP as the residual term of the Cobb-Douglas production function after removing capital (purchase of new machinery, vehicles and equipment), labour (cost of labour including wages, salaries, bonuses, social security payments) and intermediate goods (cost of raw materials and intermediate materials) from output (total sales); however, the large number of missing values reduced the number of observations by 67.2 per cent (3,386 out of 5,032). Hence, labour productivity is used as a proxy for firm productivity.

(12.) For example: ISO 9000 or 14000, or HACCP.

(13.) Evaluating financial obstacles through on self-reporting is not optimal, but it presents useful information on the financial condition of firms.

(14.) Using the censoring method, Tobit can effectively solve the zero trade problem. Although this is a simple approach, its major criticism is that it lacks a solid theoretical foundation.

(15.) Ad hoc solution attempts to solve the zero trade problem by adding a very small number (such as 0.0001) to the dependent variable or trade flow, because log (0) is undefined but log (0 + 0.0001) is not. The advantage of this method is that it is fairly simple (that is probably why it is often used in policy research), but it, too, does not have much of a theoretical basis, and produces biased results.

(16.) Heckman's sample selection model considers firms' export decision as a two-stage process, or in the form of two equations (first to decide whether to export; second to decide how much to export) for consideration. Its merit rests on the underlying rationality of export decision and theoretical support, but the method faces criticism for generating potentially biased coefficients and because of problems related to exclusion restrictions.

(17.) The standard Poisson model is prone for problems of over-dispersion and excess zero flows, because it assumes equi-dispersion (Burger, Oort and Linders 2009). A negative binomial regression can be used when there is overdispersion due to excess zero values.

(18.) Rather than taking the logarithmic form of the dependent variable (which cannot be zero), PPML assumes the dependent variable as a Poisson distribution and counts the data, and then takes a maximum likelihood estimation approach to generate the coefficient. It solves the problem, has the least amount of bias, and takes heterogeneity into consideration. However, it is criticized for producing a potential bias in the case of over-dispersion in the dependent variable. Santo Silva and Tenreyro (2011) defended the model with new evidence.

(19.) See Arvis and Shepherd (2011).

(20.) Authors have also checked for fixed effects, but the results were not significant. The low data frequency (six-year gap between two time periods, except for Laos) means that many firm-specific variables probably have changed dramatically over time.

(21.) Using labour productivity instead of TFP is a limitation of this study. The reasons are explained above.

(22.) The exchange rate is the local currency units per US dollar, and a lower value indicates appreciation of the local currency. Consistent with REER, all four ASEAN countries saw a clear and steady appreciation measured in US$ terms--except Indonesia, whose currency was more volatile from 2005 to 2015.

(23.) SMEs are defined as companies with the number of employees below 100.

(24.) The survey question is whether the firm is a part of a larger firm. If the answer is yes, we consider it as a conglomerate or domestic affiliation.

(25.) A portion of the material inputs or supplies are of foreign origin.

(26.) Authors replaced firm size, labour productivity and financial obstacles with their lagged terms and ran several regressions. Results showed that lagged labour productivity has a positive and significant coefficient, while the coefficients of firm size and financial obstacles are not significant.

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Yizhe Daniel Xie and Youngmin Baek

Yizhe Daniel Xie is Economist at SPX International Asset Management, 4th Floor, 1 New Burlington Palace. Mayfair, London, WIS 2HR, United Kingdom; email: daniel.xie@spxuk.com

Youngmin Baek is Assistant Professor at the Institute of Asia-Pacific Studies, Waseda University, Japan, 7F, Nishi-Waseda Bldg,1-21-1, Nishi-waseda, Shinjyuku-ku, Tokyo, 169-0051, Japan; email: bake@aoni.waseda.jp

DOI: 10.1355/ae37-2e
TABLE 1
Observations Tabulated by Country and Year

Survey Year  Indonesia  Laos  The Philippines  Vietnam  Total

2009           412       95     319              273      1,099
2012             0      113       0                0        113
2015         1,312        0   1,184              965      3,461
2016             0      359       0                0        359
Total        1,724      567   1,503            1,238      5,032

Source: World Bank.

TABLE 2
Summary Statistics

Variables            Obs.   Mean        Std. Dev.   Min

Whole
Real Export          5,032  9.35E+12    1.17E+14    0
REER                 5,032  116.8197    19.08106    95.5
REER Vol             5,032  1.825957    0.9447247   1.021272
NEER                 5,032  91.76524    15.70303    76.5
NEER Vol             5,032  1.46811     0.8955019   0.8305811
USD ER               5,032  9760.7      7539.846    44.32329
Firm Size            5,032  138.4607    553.3707    1
Labour Productivity  5,032  1680000000  2.68E+10    2222.222
Foreign Ownership    5,032  0.1474563   0.3545954   0
Quality Certificate  5,032  0.1899841   0.3923273   0
Financial Obstacles  4,877  0.9885175   1.131559    0
Exporters
Real Export          1,219  3.86E+13    2.34E+14    7268851
REER                 1.219  117.4189    16.78604    95.5
REER Vol             1,219  1.768429    0.9352878   1.021272
NEER                 1,219  91.55792    14.22824    76.5
NEER Vol             1,219  1.427388    0.8745037   0.8305811
USD ER               1,219  9796.63     8218.27     44.32329
Firm Size            1,219  322.0541    756.2823    1
Labour Productivity  1,219  2000000000  9390000000  3785.714
Foreign Ownership    1,219  0.3798195   0.485541    0
Quality Certificate  1,219  0.4019688   0.4904969   0
Financial Obstacles  1.187  0.8803707   1.086097    0
Non-exporters
Real Export          3,813  0           0           0
REER                 3,813  116.6281    19.75683    95.5
REER Vol             3,813  1.844348    0.9471066   1.021272
NEER                 3,813  91.83152    16.14731    76.5
NEER Vol             3,813  1.481128    0.9018369   0.8305811
USD ER               3,813  9749.213    7310.799    44.32329
Firm Size            3,813  79.76659    455.154     1
Labour Productivity  3,813  1580000000  3.03E+10    2222.222
Foreign Ownership    3,813  0.0731707   0.2604507   0
Quality Certificate  3,813  0.1222135   0.3275752   0
Financial Obstacles  3,690  1.023306    1.143771    0

Variables            Max

Whole
Real Export          5.12E+15
REER                 163.7
REER Vol             4.298595
NEER                 129.7
NEER Vol             4.053859
USD ER               21148
Firm Size            17000
Labour Productivity  1.72E+12
Foreign Ownership    1
Quality Certificate  1
Financial Obstacles  4
Exporters
Real Export          5.12E+15
REER                 163.7
REER Vol             4.298595
NEER                 129.7
NEER Vol             4.053859
USD ER               21148
Firm Size            9000
Labour Productivity  1.27E+11
Foreign Ownership    1
Quality Certificate  1
Financial Obstacles  4
Non-exporters
Real Export          0
REER                 163.7
REER Vol             4.298595
NEER                 129.7
NEER Vol             4.053859
USD ER               21148
Firm Size            17000
Labour Productivity  1.72E+12
Foreign Ownership    1
Quality Certificate  1
Financial Obstacles  4

Source: World Bank and Beruegel.

TABLE 3
Export Participation Rate by Year

Year                       2009           2012          2015

Number of exporter         304            32            834
Number of non-exporter     795            81            2,627
Export participation rate    0.276615105   0.283185841   0.240970818

Year                       2016

Number of exporter          49
Number of non-exporter     310
Export participation rate    0.136490251

Source: World Bank.

TABLE 4
Export Participation Rate by Country

Country                    Indonesia       Laos

Number of exporter           317            96
Number of non-exporter     1,407           471
Export participation rate      0.18387471    0.169312169

Country                    The Philippines  Vietnam

Number of exporter           426            380
Number of non-exporter     1,077            858
Export participation rate      0.283433134    0.306946688

Source: World Bank.

TABLE 5
Export Participation Rate by Sector

Sector         Industry                             ISIC
                                                    Sector  Non-exporter
                                                    Code    #

Manufacturing  Electronics (31&32)                  32          0
Manufacturing  Precision instruments                33          2
Manufacturing  Electronics (31&32)                  31         82
Manufacturing  Garments                             IK        281
Manufacturing  Transport machines (34 &35)          35          6
Manufacturing  Wood                                 20         31
Manufacturing  Leather                              19         22
Manufacturing  Tobacco                              16         13
Manufacturing  Machinery and equipment (29&30)      29         37
Manufacturing  Forestry and logging                  2         35
Manufacturing  Chemicals                             2-4      256
Manufacturing  Food                                 15        440
Manufacturing  Furniture                            36        43
Manufacturing  Plastics & rubber                    25        268
Manufacturing  Textiles                             17        176
Manufacturing  Paper                                21         14
Manufacturing  Fabricated metal products            2S        230
Manufacturing  Transport machines (34 &35)          34         11
Manufacturing  Non metallic mineral products        26        283
Manufacturing  Publishing, pringting, and Recorded  22         39
               media
Manufacturing  Basic metals                         27         24
Manufacturing  Fishing and aquaculture               3         32
Manufacturing  Refined petroleum product            23         11
Manufacturing  Machinery and equipment (29&30)      30          1
Manufacturing  Recycling                            37          6
Service        Transport section I: (60-64)         61          1
Service        Transport section I: (60-64)         63         12
Service        IT                                   72         10
Service        Wholesales                           51        102
Service        Hotel and restaurants: section H     55        126
Service        Transport section I: (60-64)         64          7
Service        Services of motor vehicles           50         35
Service        Retail                               52        461
Service        Transport section I: (60-64)         60         52
Service        Construction Selection F:            45        115
Service        Transport section I: (60-64)         62          1
               Total                                        3,265

Sector         Exporter  Total     Exporter
               #         #         Participation
                                   Rate

Manufacturing    1           1     100%
Manufacturing    2           4      50.00%
Manufacturing   68         150      45.33%
Manufacturing  189         470      40.21%
Manufacturing    4          10      40.00%
Manufacturing   19          50      38.00%
Manufacturing    9          31      29.03%
Manufacturing    5          18      27.78%
Manufacturing   14          51      27.45%
Manufacturing   13          48      27.08%
Manufacturing   XS         344      25.58%
Manufacturing  151         591      25.55%
Manufacturing   14          57      24.56%
Manufacturing   X7         355      24.51%
Manufacturing   54         230      23.48%
Manufacturing    4          18      22.22%
Manufacturing   64         294      21.77%
Manufacturing    3          14      21.43%
Manufacturing   74         357      20.73%
Manufacturing    7          46      15.22%

Manufacturing    3          27      11.11%
Manufacturing    3          35       8.57%
Manufacturing    1          12       8.33%
Manufacturing    0           1       0%
Manufacturing    0           6       0%
Service          1           2      50%
Service          3          15      20%
Service          2          12      16.67%
Service         16         118      13.56%
Service         IX         144      12.50%
Service          1           8      12.50%
Service          3          38       7.89%
Service         39         500       7.80%
Service          3          55       5.45%
Service          4         119       3.36%
Service          0           1       0%
               967       4,232      22.85%

Source: World Bank.

TABLE 6
Description of Dependent and Independent Variables

     Variable

Y    Real Export
X1   REER
X2   ER Vol
X3   Firm Size
X4   Labour Productivity
X5   Quality Certificate
X6   Foreign Ownership
X7   Financial Obstacles
X8   FE Year
X9   FE Country
X10  FE Industry

     Description

Y    Firm's export deflated by GDP change of deflator
X1   Interest variable: Real Effective Exchange Rate
X2   Control Variable: The standard deviation of the first
     difference of logorithm of monthly exchange rate in year t
X3   Control firm's characteristics: Number of total employees
X4   Control firm's characteristics: Firm's total sales divided by
     number of employees
X5   Control firm's characteristics: Dummy variable (1 for
     a firm which has an internationally recognized quality
     certification, 0 otherwise)
X6   Control firm's characteristics: Dummy variable (1 for a
     firm which has foreign shareholders, 0 otherwise)
X7   Control firm's characteristics: Self evaluated obstacles in
     access to finance (5 degrees 0-4, 0 means no obstacles,
     4 means very severe obstacle)
X8   Fixed Effects, Dummy variable: survey year
X9   Fixed Effects, Dummy variable: country in where the firm
     belongs to
X10  Fixed Effects, Dummy variable: industry that a firm
     belongs to at the survey year (completed before the
     interview)

TABLE 7
Number of Exporters and Non-exporters

Status        Real Export  Number of firms  Percentage

Exporter      Y> 0         1,219             24.22
Non-exporter  Y=0          3,813             75.78
              Total        5,032            100

TABLE 8
Baseline Analysis Results Using Five Different Models

                         (1)            (2)            (3)
                         OLS            Tobit          Ad Hoc: OLS
                         Y=Log Real     Y=Export       Y=Log Real

VARIABLES                Export         Participation  Export

                                        Ratio: 0-100   (+0.0001)
REER                     -0.0330 (***)  -2.571 (***)   -0.286 (***)
                         (0.00866)      (0.562)        (0.0616)
ER Volatility            -0.688 (**)    -144.5 (***)   -14.26 (***)
                         (0.302)        (18.52)        (1.848)
Firm Size                0.00119 (***)  0.0315 (***)   0.00514 (***)
                         (0.000141)     (0.00377)      (0.00168)
Log Labour Productivity  1.082 (***)    (0.00377)      1.738 (***)
                         (0.0233)       13.21 (***)    (0.165)
Foreign Ownership                       (1.526)
Constant                 12.84 (***)    558.9 (***)    55.00 (***)
                         (1.846)        (112.9)        (11.76)
Sigma                                   124.7 (***)
                                        (4.318)
Lambda
Over-dispersion Test
(Prob>=Chi-bar-squared)
Observations             967            4,232          4,232
R-squared                0.861                         0.144
Year FE                  Yes            Yes            Yes
Country FE               Yes            Yes            Yes
Industry FE              Yes            Yes            Yes

                         (4)             (5)
                         Heckman Sample  Selection Model
                         Y=Log Real      Y = Dummy
VARIABLES                Export          Export
                         Outcome Eq      Selection Eq

REER                     -0.00882        -0.00328
                         (0.00992)       (0.00507)
ER Volatility            0.469           -0.593 (***)
                         (0.353)         (0.164)
Firm Size                0.00101 (***)   0.000206 (***)
                         (7.06e-05)      (3.50e-05)
Log Labour Productivity  0.973 (***)     0.0868 (***)
                         (0.0293)        (0.0134)
Foreign Ownership                        1.122 (***)
                                         (0.0649)
Constant                 8.805 (***)     0.605
                         (2.010)         (1.019)
Sigma
Lambda                                   -1.159 (***)
                                         (0.150)
Over-dispersion Test
(Prob>=Chi-bar-squared)
Observations             4,232           4,232
R-squared
Year FE                  Yes             Yes
Country FE               Yes             Yes
Industry FE              Yes             Yes

                         (6)             (7)
                         NB              PPML
                         Y=Real          Y = Real
VARIABLES                Export          Export

REER                     -0.0639 (*)     -0.421 (***)
                         (0.03323)       (0.00907)
ER Volatility            -2.701 (**)     -0.728 (***)
                         (1.056)         (0.182)
Firm Size                0.007540 (***)  0.000410 (***)
                         (0.00132)       (7.57e-05)
Log Labour Productivity  1 232 (***)     0.780 (***)
                         (0.0904)        (0.0615)
Foreign Ownership
Constant                 19.970 (***)    19.12 (***)
                         (2.265)         (2.265)
Sigma
Lambda
Over-dispersion Test     0.000
(Prob>=Chi-bar-squared)
Observations             4,232           4,224
R-squared                0.007           0.209
Year FE                  Yes             Yes
Country FE               Yes             Yes
Industry FE              Yes             Yes

Note: Export participation is measured as the overseas sales ratio,
and its value is between 0 and 100. For Tobit, the left-censoring
point is Export Participation = 0 and right-censoring point is Export
Participation = 100. In the ad hoc method, 0.0001 is added to every
value of Y to avoid an undefined value of log zero, and then pooled
OLS is used for regression. Robust standard errors in parentheses,
(***) p < 0.01, (**) p < 0.05, (*) p < 0.1.
Source: Authors' calculations.

TABLE 9
Analysis Results of Extending the Baseline Analysis to Include More
Firm-Specific Variables

VARIABLES                (1)             (2)             (3)
                         PPML            PPML            PPML

REER                     -0.0421 (***)   -0.0400 (***)   -0.0294 (***)
                         (0.00907)       (0.00924)       (0.00967)
ER Volatility            -0.728 (***)    -0.573 (***)    -0.533 (***)
                         (0.182)         (0.203)         (0.192)
Firm Size                0.000410 (***)  0.000350 (***)  0.000402 (***)
                         (7.57e-05)      (7.1 le-05)     (6.84e-05)
Log Labour Productivity  0.780 (***)     0.737 (***)     0.713 (***)
                         (0.0615)        (0.0643)        (0.0606)
Foreign Ownership                        0.988 (***)     0.523*
                                         (0.368)         (0.289)
Quality Certificate                                      1.681 (***)
                                                         (0.586)
Financial Obstacles
Constant                 19.12 (***)     18.61 (***)     16.78 (***)
                         (2.265)         (2.383)         (2.489)
Observations             4,224           4,224           4,224
R-squared                0.209           0.307           0.479
Year FE                  Yes             Yes             Yes
Country FE               Yes             Yes             Yes
Industry FE              Yes             Yes             Yes

VARIABLES                (4)
                         PPML

REER                     -0.0252 (***)
                         (0.00903)
ER Volatility            -0.477 (**)
                         (0.189)
Firm Size                0.000405 (***)
                         (6.23e-05)
Log Labour Productivity  0.732 (***)
                         (0.0567)
Foreign Ownership        0.517 (*)
                         (0.287)
Quality Certificate      1.434 (**)
                         (0.583)
Financial Obstacles      -0.432 (***)
                         (0.164)
Constant                 16.17 (***)
                         (2.314)
Observations             4,093)
R-squared                0.547
Year FE                  Yes
Country FE               Yes
Industry FE              Yes

Note: Robust standard errors in parentheses,
(***) p < 0.01. (**) p < 0.05, (*) p < 0.1.
Source: Authors' calculations.

TABLE 10
Robustness Check Replacing REER with NEER

VARIABLES                (1)             (2)             (3)
                         PPML            PPML            PPML

NEER                     -0.0434 (***)   -0.422 (***)    -0.0300 (***)
                         (0.00985)       (0.00996)       (0.0105)
NEER Vol                 -0.343**        -0.220          -0.262 (*)
                         (0.134)         (0.151)         (0.139)
Firm Size                0.000410 (***)  0.000350 (***)  0.000402 (***)
                         (7.57e-05)      (7.11e-05)      (6.84e-05)
Log Labour Productivity  0.780 (***)     0.737 (***)     0.713 (***)
                         (0.0615)        (0.0643)        (0.0606)
Foreign Ownership                        0.988 (***)     0.523 (*)
                                         (0.368)         (0.289)
Quality Certificate                                      1.681 (***)
                                                         (0.586)
Financial Obstacle
Constant                 17.30 (***)     17.06 (***)     15.48 (***)
                         (1.957)         (2.038)         (2.136)
Observations             4,224           4,224           4,224
R-squared                0.209           0.307           0.479
Year FE                  Yes             Yes             Yes
Country FE               Yes             Yes             Yes
Industry FE              Yes             Yes             Yes

VARIABLES                (4)
                         PPML

NEER                     -0.0256 (***)
                         (0.00982)
NEER Vol                 -0.242 (*)
                         (0.142)
Firm Size                0.000405 (***)
                         (6.23e-05)
Log Labour Productivity  0.732 (***)
                         (0.0567)
Foreign Ownership        0.517 (*)
                         (0.287)
Quality Certificate      1.434 (**)
                         (0.583)
Financial Obstacle       -0.432 (***)
                         (0.164)
Constant                 15.02 (***)
                         (1.986)
Observations             4,093
R-squared                0.547
Year FE                  Yes
Country FE               Yes
Industry FE              Yes

Note: Robust standard errors in parentheses,
(***) p < 0.01, (**) p < 0.05, (*) p < 0.1.
Source: Authors' calculations.

TABLE 11
Robustness Check Replacing REER with US dollar

VARIABLES                (1)             (2)             (3)
                         PPML            PPML            PPML

USD                      0.000132 (**)   0.000144 (***)  0.000133 (***)
                         (5.25e-05)      (5.02e-05)      (5.10e-05)
Firm Size                0.000410 (***)  0.000350 (***)  0.000402 (***)
                         (7.57e-05)      (7.11e-05)      (6.84e-05)
Log Labour Productivity  0.780 (***)     0.737 (***)     0.713 (***)
                         (0.0615)        (0.0643)        (0.0606)
Foreign Ownership                        0.988 (***)     0.523*
                                         (0.368)         (0.289)
Quality Certificate                                      1.681 (***)
                                                         (0.586)
Financial Obstacles
Constant                 10.68 (***)     10.94 (***)     10.40 (***)
                         (1.060)         (1.009)         (1.035)
Observations             4,224           4,224           4,224
R-squared                0.209           0.307           0.479
Year FE                  Yes             Yes             Yes
Country FE               Yes             Yes             Yes
Industry FE              Yes             Yes             Yes

VARIABLES                (4)
                         PPML

USD                      0.000132 (***)
                         (4.93e-05)
Firm Size                0.000405 (***)
                         (6.23e-05)
Log Labour Productivity  0.732 (***)
                         (0.0567)
Foreign Ownership        0.517 (*)
                         (0.287)
Quality Certificate      1.434 (**)
                         (0.583)
Financial Obstacles      -0.432 (***)
                         (0.164)
Constant                 10.43 (***)
                         (1.001)
Observations             4,093
R-squared                0.547
Year FE                  Yes
Country FE               Yes
Industry FE              Yes

Note: USS stands for the local currency unit per dollar; a smaller
value indicates the appreciation of local currency. Because of
unavailability of data on monthly exchange rates in the four ASEAN
countries, exchange rate volatility is not included as a control
variable. Robust standard errors in parentheses,
(***) p < 0.01, (**) p < 0.05, (*) p < 0.1.
Source: Authors' calculations.

TABLE 12
Robustness Check by Decomposing the Data into Manufacturing and
Services

VARIABLES                (1)             (2)             (3)
                         Manufacturing   Manufacturing   Manufacturing

REER                     -0.351 (***)    -0.0219 (**)    -0.0182 (**)
                         (0.00952)       (0.00978)       (0.00919)
ER Volatility            -0.521 (***)    -0.479 (**)     -0.429 (**)
                         (0.202)         (0.189)         (0.184)
Firm Size                0.000349 (***)  0.000402 (***)  0.000405 (***)
                         (7.17e-05)      (7.02e-05)      (6.43e-05)
Log Labour Productivity  0.773 (***)     0.745 (***)     0.762 (***)
                         (0.0655)        (0.0630)        (0.0595)
Foreign Ownership        0.975 (***)     0.509 (*)       0.505 (*)
                         (0.375)         (0.289)         -0.286
Quality Certificate                      1 734 (***)     1.538 (**)
                                         (0.671)         (0.662)
Financial Obstacles                                      -0.382 (**)
                                                         (0.155)
Constant                 19 27 (***)     18.35 (***)     17.46 (***)
                         (2.697)         (2.553)         (2.292)
Observations             3,155           3,155           3,055
R-squared                0.307           0.483           0.554
Year FE                  Yes             Yes             Yes
Country FE               Yes             Yes             Yes
Industry FE              Yes             Yes             Yes

VARIABLES                (4)            (5)            (6)
                         Services       Services       Services

REER                     -0.0975 (***)  -0.0967 (***)  -0.0583 (***)
                         (0.0150)       (0.0152)       (0.0200)
ER Volatility            -2.225 (***)   -2 195 (***)   -1.559 (**)
                         (0.527)        (0.523)        (0.679)
Firm Size                0.00253        0.00254        0.00123 (***)
                         (0.00555)      (0.00595)      (0.000282)
Log Labour Productivity  0.416 (***)    0.418 (***)    0.959 (***)
                         (0.0969)       (0.0944)       (0.115)
Foreign Ownership        -1.453         -1.517         -2.080
                         (5.533)        (5.449)        (1.646)
Quality Certificate                     0.347          -1.651 (***)
                                        (0.811)        (0.336)
Financial Obstacles                                    -3.189 (***)
                                                       (0.694)
Constant                 34.74 (***)    34.53 (***)    15.65 (***)
                         (3.588)        (3.429)        (4.736)
Observations             986            986            957
R-squared                0.245          0.258          0.980
Year FE                  Yes            Yes            Yes
Country FE               Yes            Yes            Yes
Industry FE              Yes            Yes            Yes

Note: Robust standard errors in parentheses,
(***) p < 0.01, (**) p < 0.05, (*) p < 0.1.
Source: Authors' calculations.

TABLE 13
Analysis Results by Adding an Interaction Term between SME Dummy and
REER/ER Volatility

VARIABLES                (1)             (2)             (3)
                         PPML            PPML            PPML

REER                     -0.250 (***)    -0.0341 (***)   -0.0245 (***)
                         (0.00879)       (0.00908)       (0.00888)
SME*REER                 -0.694 (***)                    -0.664 (***)
                         (0.0945)                        (0.100)
ER Volatility            -0.695 (***)    -0.699 (***)    -0.644 (***)
                         (0.233)         (0.235)         (0.236)
SME*ER Volatility                        -1.498 (***)
                                         (0.225)
Firm Size                0.000334 (***)  0.000348 (***)  0.000322 (***)
                         (6.73e-05)      (6.60e-05)      (6.49e-05)
Log Labour Productivity  0.862 (***)     0.863 (***)     0.842 (***)
                         (0.0639)        (0.0642)        (0.0693)
Foreign Ownership                                        0.25
                                                         (0.299)
Quality Certificate
Financial Obstacles
Constant                 16.29 (***)     17 19 (***)     16.28 (***)
                         (2.530)         (2.506)         (2.572)
Observations             4,224           4,224           4,224
R-squared                0.482           0.486           0.485
Year FE                  Yes             Yes             Yes
Country FE               Yes             Yes             Yes
Industry FE              Yes             Yes             Yes

VARIABLES                (4)             (5)             (6)
                         PPML            PPML            PPML

REER                     -0.0333 (***)   -0.0222 (**)    -0.0292 (***)
                         (0.00915)       (0.00885)       (0.00922)
SME*REER                                 -0.589 (***)
                                         (0.111)
ER Volatility            -0.645 (***)    -0.597 (***)    -0.592 (***)
                         (0.241)         (0.199)         (0.202)
SME*ER Volatility        -1.431 (***)                    -1.244 (***)
                         (0.243)                         (0.264)
Firm Size                0.000336 (***)  0.000346 (***)  0.000359 (***)
                         (6.39e-05)      (6.53e-05)      (6.35e-05)
Log Labour Productivity  0.842 (***)     0.808 (***)     0.806 (***)
                         (0.0700)        (0.0725)        (0.0727)
Foreign Ownership        0.251           0.0897          0.0846
                         (0.305)         (0.281)         (0.287)
Quality Certificate                      0.824           0.887 (*)
                                         (0.519)         (0.534)
Financial Obstacles
Constant                 17.15 (***)     15.88 (***)     16.53 (***)
                         (2.549)         (2.478)         (2.480)
Observations             4,224           4,224           4,224
R-squared                0.490           0.533           0.540
Year FE                  Yes             Yes             Yes
Country FE               Yes             Yes             Yes
Industry FE              Yes             Yes             Yes

VARIABLES                (7)             (8)
                         PPML            PPML

REER                     -0.0177 (**)    -0.0243 (***)
                         (0.00799)       (0.00841)
SME*REER                 -0.575 (***)
                         (0.0942)
ER Volatility            -0.526 (***)    -0.520 (***)
                         (0.190)         (0.192)
SME*ER Volatility                        -1 213 (***)
                                         (0.230)
Firm Size                0.000349 (***)  0.000362 (***)
                         (5.91e-05)      (5.79e-05)
Log Labour Productivity  0.828 (***)     0.824 (***)
                         (0.0645)        (0.0644)
Foreign Ownership        0.0882          0.0847
                         (0.272)         (0.278)
Quality Certificate      0.685           0.751
                         (0.480)         (0.495)
Financial Obstacles      -0.408 (***)    -0.407 (***)
                         (0.145)         (0.145)
Constant                 15.04 (***)     15.69 (***)
                         (2.213)         (2.216)
Observations             4,093           4,093
R-squared                0.629           0.635
Year FE                  Yes             Yes
Country FE               Yes             Yes
Industry FE              Yes             Yes

Note: Robust standard errors in parentheses,
(***) p < 0.01, (**) p < 0.05, (*) p < 0.1.
Source: Authors' calculations.

TABLE 14
Analysis Results by Adding an Interaction Term between Export-before
Dummy and REER/ER Volatility

VARIABLES                    (1)             (2)
                             PPML            PPML

REER                         -0.0319 (***)   -0.0263 (***)
                             (0.00610)       (0.00837)
Export Before*REER           1.047 (***)
                             (0.280)
ER Volatility                -0.620 (***)    -3.087 (***)
                             (0.122)         (0.956)
Export Before & ER Volality                  2.443**
                                             (0.982)
Firm Size                    0.000577 (***)  0.000486 (***)
                             (7.35e-05)      (7.31e-05)
Log Labour Productivity      0.831 (***)     0.833 (***)
                             (0.0463)        (0.0468)
Foreign Ownership
Quality Certificate
Financial Obstacle
Constant                     12.20 (***)     16.58 (***)
                             (2.517)         (1.966)
Observations                 4,224           4,224
R-squared                    0.789           0.740
Year FE                      Yes             Yes
Country FE                   Yes             Yes
Industry FE                  Yes             Yes

VARIABLES                    (3)             (4)
                             PPML            PPML

REER                         -0.0312 (***)   -0.0257 (***)
                             (0.00617)       (0.00852)
Export Before*REER           1.049 (***)
                             (0.292)
ER Volatility                -0.573 (***)    -3.054 (***)
                             (0.127)         (0.993)
Export Before & ER Volality                  2,444 (**)
                                             (1.017)
Firm Size                    0.000570 (***)  0.000480 (***)
                             (7.63e-05)      (7.47e-05)
Log Labour Productivity      0.819 (***)     0.824 (***)
                             (0.0500)        (0.0516)
Foreign Ownership            0.200           0.147
                             (0.194)         (0.216)
Quality Certificate
Financial Obstacle
Constant                     12.02 (***)     16.46 (***)
                             (2.573)         (1.984)
Observations                 4,224           4,224
R-squared                    0.784           0.736
Year FE                      Yes             Yes
Country FE                   Yes             Yes
Industry FE                  Yes             Yes

VARIABLES                    (5)             (6)
                             PPML            PPML

REER                         -0.0333 (***)   -0.0259 (***)
                             (0.00681)       (0.00869)
Export Before*REER           1.106 (***)
                             (0.304)
ER Volatility                -0.597 (***)    -3.076 (***)
                             (0.150)         (1.036)
Export Before & ER Volality                  2.464 (**)
                                             (1.051)
Firm Size                    0.000583 (***)  0.000480 (***)
                             (7.89e-05)      (7.66e-05)
Log Labour Productivity      0.839 (***)     0.827 (***)
                             (0.0522)        (0.0574)
Foreign Ownership            0.270           0.156
                             (0.191)         (0.208)
Quality Certificate          -0.319          -0.0428
                             (0.254)         (0.319)
Financial Obstacle
Constant                     11.88 (***)     16.47 (***)
                             (2.676)         (1.995)
Observations                 4,224           4,224
R-squared                    0.794           0.737
Year FE                      Yes             Yes
Country FE                   Yes             Yes
Industry FE                  Yes             Yes

VARIABLES                    (7)             (8)
                             PPML            PPML

REER                         -0.0320 (***)   -0.0252 (***)
                             (0.00678)       (0.00852)
Export Before*REER           1.064 (***)
                             (0.310)
ER Volatility                -0.568 (***)    -2 929 (***)
                             (0.138)         (1.010)
Export Before & ER Volality                  2.348 (**)
                                             (1.018)
Firm Size                    0.000572 (***)  0.000474 (***)
                             (7.79e-05)      (7.24e-05)
Log Labour Productivity      0.832 (***)     0.816 (***)
                             (0.0549)        (0.0609)
Foreign Ownership            0.269           0.161
                             (0.196)         (0.216)
Quality Certificate          -0.311          -0.0410
                             (0.251)         (0.312)
Financial Obstacle           -0.126          -0.171 (*)
                             (0.0947)        (0.103)
Constant                     12.02 (***)     16.55 (***)
                             (2.701)         (2.034)
Observations                 4,093           4,093
R-squared                    0.793           0.741
Year FE                      Yes             Yes
Country FE                   Yes             Yes
Industry FE                  Yes             Yes

Note: Robust standard errors in parentheses,
(***) p < 0.01, (**) p < 0.05, (*) p < 0.1.
Source: Authors' calculations.

TABLE 15
Analysis Results by Adding an Interaction Term between Foreign
Ownership Dummy and REER/ER Volatility

VARIABLES                (1)             (2)             (3)
                         PPML            PPML            PPML

REER                     -0.0405 (***)   -0.0406 (***)   -0.0296 (***)
                         (0.00926)       (0.00974)       (0.00965)
Foreign*REER             0.211 (***)                     0.110 (*)
                         (0.0793)                        (0.0620)
ER Volatility            -0.576 (***)    -0.758 (***)    -0.536 (***)
                         (0.203)         (0.250)         (0.191)
Foreign*ER Volatility                    0.460 (***)
                                         (0.161)
Firm Size                0.000347 (***)  0.000366 (***)  0.000401 (***)
                         (7.15e-05)      (6.97e-05)      (6.87e-05)
Log Labour Productivity  0.738 (***)     0.739 (***)     0.713 (***)
                         (0.0643)        (0.0641)        (0.0606)
Quality Certificate                                      1.685 (***)
                                                         (0.587)
Financial Obstacle
Constant                 18.68 (***)     18.71 (***)     16.82 (***)
                         (2.385)         (2.609)         (2.479)
Observations             4,224           4,224           4,224
R-squared                0.305           0.315           0.478
Year FE                  Yes             Yes             Yes
Country FE               Yes             Yes             Yes
Industry FE              Yes             Yes             Yes

VARIABLES                (4)             (5)             (6)
                         PPML            PPML            PPML

REER                     -0.0295 (***)   -0.0255 (***)   -0.0256 (***)
                         (0.00989)       (0.00900)       (0.00936)
Foreign*REER                             0.109 (*)
                                         (0.0620)
ER Volatility            -0.628 (***)    -0.480 (**)     -0.587 (***)
                         (0.208)         (0.188)         (0.218)
Foreign*ER Volatility    0.254 (**)                      0.248 (**)
                         (0.128)                         (0.126)
Firm Size                0.000408 (***)  0.000404 (***)  0.000412 (***)
                         (6.76e-05)      (6.25e-05)      (6.15e-05)
Log Labour Productivity  0.713 (***)     0.733 (***)     0.734 (***)
                         (0.0605)        (0.0566)        (0.0565)
Quality Certificate      1.669 (***)     1.437 (**)      1.428 (**)
                         (0.583)         (0.584)         (0.581)
Financial Obstacle                       -0.432 (***)    -0.430 (***)
                                         (0.164)         (0.163)
Constant                 16.77 (***)     16.21 (***)     16.21 (***)
                         (2.597)         (2.305)         (2.465)
Observations             4,224           4,093           4,093
R-squared                0.483           0.546           0.552
Year FE                  Yes             Yes             Yes
Country FE               Yes             Yes             Yes
Industry FE              Yes             Yes             Yes

Note: Robust standard errors in parentheses,
(***) p < 0.01, (**) p < 0.05, (*) p < 0.1.
Source: Authors' calculations.

TABLE 16
Analysis Results by Adding an Interaction Term between Conglomerate
Dummy and REER/ER Volatility

VARIABLES                   (1)             (2)
                            PPML            PPML

REER                        -0.0421 (***)   -0.0380 (***)
                            (0.00832)       (0.00930)
Conglomerate*REER           0.0141 (***)
                            (0.00243)
ER Volatility               -0.520 (***)    -0.891 (***)
                            (0.187)         (0.281)
Conglomerate*ER Volatility                  0.645 (***)
                                            (0.121)
Size                        0.000419 (***)  0.000399 (***)
                            (6.57e-05)      (6.49e-05)
Log Labour Productivity     0.765 (***)     0.770 (***)
                            (0.0544)        (0.0567)
Foreign Ownership
Quality Certificate
Financial Obstacle
Constant                    18.17 (***)     18.51 (***)
                            (2.196)         (2.577)'
Observations                4,224           4,224
R-squared                   0.517           0.492
Year FE                     Yes             Yes
Country FE                  Yes             Yes
Industry FE                 Yes             Yes

VARIABLES                   (3)             (4)
                            PPML            PPML

REER                        -0.0397 (***)   -0.0366 (***)
                            (0.00851)       (0.00918)
Conglomerate*REER           0.0127 (***)
                            (0.00292)
ER Volatility               -0.452 (**)     -0.758 (***)
                            (0.191)         (0.287)
Conglomerate*ER Volatility                  0.566 (***)
                                            (0.146)
Size                        0.000389 (***)  0.000371 (***)
                            (6.42e-05)      (6.47e-05)
Log Labour Productivity     0.743 (***)     0.746 (***)
                            (0.0590)        (0.0620)
Foreign Ownership           0.484           0.482
                            (0.324)         (0.355)
Quality Certificate
Financial Obstacle
Constant                    17.91 (***)     18.23 (***)
                            (2.269)         (2.557)
Observations                4,224           4,224
R-squared                   0.501           0.479
Year FE                     Yes             Yes
Country FE                  Yes             Yes
Industry FE                 Yes             Yes

VARIABLES                   (5)             (6)
                            PPML            PPML

REER                        -0.0321 (***)   -0.0272 (***)
                            (0.00922)       (0.00969)
Conglomerate*REER           0.0101 (***)
                            (0.00303)
ER Volatility               -0.403 (**)     -0.644 (**)
                            (0.186)         (0.278)
Conglomerate*ER Volatility                  0.470 (***)
                                            (0.138)
Size                        0.000416 (***)  0.000402 (***)
                            (6.20e-05)      (6.21e-05)
Log Labour Productivity     0.709 (***)     0.712 (***)
                            (0.0599)        (0.0617)
Foreign Ownership           0.294           0.248
                            (0.271)         (0.288)
Quality Certificate         1.354 (**)      1.466 (**)
                            (0.634)         (0.621)
Financial Obstacle
Constant                    16.75 (***)     16.69 (***)
                            (2.383)         (2.688)
Observations                4,224           4,224
R-squared                   0.569           0.562
Year FE                     Yes             Yes
Country FE                  Yes             Yes
Industry FE                 Yes             Yes

VARIABLES                   (7)             (8)
                            PPML            PPML

REER                        -0.0282 (***)   -0.0239 (**)
                            (0.00876)       (0.00941)
Conglomerate*REER           0.00967 (***)
                            (0.00274)
ER Volatility               -0.354 (*)      -0.563 (**)
                            (0.183)         (0.251)
Conglomerate*ER Volatility                  0.447 (***)
                                            (0.126)
Size                        0.000417 (***)  0.000404 (***)
                            (5.72e-05)      (5.73e-05)
Log Labour Productivity     0.721 (***)     0.722 (***)
                            (0.0574)        (0.0593)
Foreign Ownership           0.286           0.254
                            (0.272)         (0.291
Quality Certificate         1.168 (**)      1.274 (**)
                            (0.588)         (0.583)
Financial Obstacle          -0.400 (***)    -0.391 (***)
                            (0.132)         (0.130)
Constant                    16.36 (***)     16.38 (***)
                            (2.351)         (2.632)
Observations                4,093           4,093
R-squared                   0.607           0.598
Year FE                     Yes             Yes
Country FE                  Yes             Yes
Industry FE                 Yes             Yes

Note: Robust standard errors in parentheses,
(***) p < 0.01, (**) p < 0.05, (*) p < 0.1.
Source: Authors' calculations.

TABLE 17
Analysis Results by Adding an Interaction Term between Foreign
Contents Dummy and REER/ER Volatility

VARIABLES                (1)             (2)             (3)
                         PPML            PPML            PPML

REER                     -0.0855         -0.0608 (***)   -0.0786 (***)
                         (0.0149)        (0.0141)        (0.0149)
Foreign Contents*REER    0.0306 (***)                    0.0277 (***)
                         (0.00513)                       (0.00508)
ER Volatility            -1.028 (***)    -2.333 (***)    -0.937 (***)
                         (0.259)         (0.685)         (0.270)
Foreign Contents*ER                      1.457 (***)
Volatility                               (0.326)
Firm Size                0.000499 (***)  0.000414 (***)  0.000462 (***)
                         (5.77e-05)      (5.68e-05)      (5.89e-05)
Log Labour Productivity  0.805 (***)     0.798 (***)     0.789 (***)
                         (0.0551)        (0.0564)        (0.0590)
Foreign Ownership                                        0.394
                                                         (0.331)
Quality Certificate
Financial Obstacle
Constant                 22.74 (***)     23.64 (***)     21.92 (***)
                         (2.918)         (3.850)         (2.965)
Observations             3,084           3,084           3,084
R-squared                0.600           0.555           0.602
Year FE                  Yes             Yes             Yes
Country FE               Yes             Yes             Yes
Industry FE              Yes             Yes             Yes

VARIABLES                (4)             (5)             (6)
                         PPML            PPML            PPML

REER                     -0.0565 (***)   -0.0643 (***)   -0.0452 (***)
                         (0.0144)        (0.0174)        (0.0165)
Foreign Contents*REER                    0.0233 (***)
                                         (0.00605)
ER Volatility            -2.077 (***)    -0.909 (***)    -1,786 (**)
                         (0.701)         (0.285)         (0.746)
Foreign Contents*ER      1.296 (***)                     1.028 (***)
Volatility               (0.331)                         (0.385)
Firm Size                0.000388 (***)  0.000457 (***)  0.000405 (***)
                         (5.81e-05)      (5.22e-05)      (5.37e-05)
Log Labour Productivity  0.782 (***)     0.747 (***)     0.739 (***)
                         (0.0606)        (0.0635)        (0.0646)
Foreign Ownership        0.399           0.193           0.196
                         (0.346)         (0.297)         (0.310)
Quality Certificate                      1.168 (*)       1.267 (*)
                                         (0.612)         (0.662)
Financial Obstacle
Constant                 22.71 (***)     20.63 (***)     21.16 (***)
                         (3.935)         (3.197)         (4.363)
Observations             3,084           3,084           3,084
R-squared                0.557           0.648           0.616
Year FE                  Yes             Yes             Yes
Country FE               Yes             Yes             Yes
Industry FE              Yes             Yes             Yes

VARIABLES                (7)             (8)
                         PPML            PPML

REER                     -0.0573 (***)   -0.0396 (**)
                         (0.0160)        (0.0157)
Foreign Contents*REER    0.0213 (***)
                         (0.00572)
ER Volatility            -0.817 (***)    -1.578 (**)
                         (0.269)         (0.708)
Foreign Contents*ER                      0.920 (**)
Volatility                               (0.369)
Firm Size                0.000450 (***)  0.000404 (***)
                         (5.04e-05)      (5.19e-05)
Log Labour Productivity  0.762 (***)     0.755 (***)
                         (0.0612)        (0.0626)
Foreign Ownership        0.194           0.204
                         (0.292)         (0.306)
Quality Certificate      1.055 (*)       1.156 (*)
                         (0.605)         (0.651)
Financial Obstacle       -0.291 (**)     -0.300 (**)
                         (0.131)         (0.131)
Constant                 19.56 (***)     19 92 (***)
                         (2.910)         (4.154)
Observations             2,989           2,989
R-squared                0.679           0.650
Year FE                  Yes             Yes
Country FE               Yes             Yes
Industry FE              Yes             Yes

Note: Robust standard errors in parentheses,
(***) p < 0.01, (**) p < 0.05, (*) p < 0.1.
Source: Authors' calculations.
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Article Details
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Author:Xie, Yizhe Daniel; Baek, Youngmin
Publication:Journal of Southeast Asian Economies
Geographic Code:9INDO
Date:Aug 1, 2020
Words:11415
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