The up technological acquisition through disembodied technology and

The relationship between international trade and productivity growth has been extensively investigated. It is always at the core of intense debates amongst academic researchers and policymakers over the past decades since the pioneering work of A. B. Bernard, Jensen, and Lawrence (1995). Since then, many empirical and theoretical studies in this field have flourished. These contributed great insights into the literature, with an intensive focus on the investigation of the relationship between characteristics of firms, especially productivity, and exporting behavior of firms. Firms that export are found in empirical studies to be better than firms that serve only domestic markets. The term “exceptional export performance” initially used by A. B. Bernard and Jensen (1999a) to describe their findings of the superiority of exporters in the U.S. manufacturing sector. Currently, this is broadly confirmed by many other researchers in different countries, implying the fact that exporters are superior to non-exporters almost everywhere. Two alternatives which are not mutually exclusive1 hypothesis have been proposed to explain the superior performance of exporters, but empirical evidence is not definitive as each of them has distinctive policy implications. The first is self-selection hypothesis which considers the post-exporting productivity effects. This implies that only the more productive ones are able to recoup the sunk costs2 of entry into foreign markets and survive in the tough foreign competition (Roberts & Tybout, 1997). An alternative explanation is learning by exporting in which exporting makes firms more productive. This is due to the fact that foreign competition and exposure can also speed up technological acquisition through disembodied technology and knowledge diffusion. This helps to achieve economies of scale and thereby improve the manufacturing process, reduce production costs and improve product quality (Almeida & Fernandes, 2008; De Loecker, 2007; Van Biesebroeck, 2005).


Both channels stated above are plausible and it is widely believed that exporters are superior to non-exporters. This can be attributed to the self-selection effect or the learning effect from exporting or both, though they vary significantly with respect to empirical methodology and measurement of firm productivity. Thus, the literature discussing the causality of an exporting-productivity relationship shows mixed findings. There are many existing empirical studies that supported the self-selection effect in both developed and developing countries. For instance, (AB Bernard & Jansen, 1999) for the US; (J. R. Baldwin & Gu, 2003) for Canada; (Arnold & Hussinger, 2005; A. B. Bernard & Wagner, 1997, 2001) for Germany; (Imbruno, 2008) for Italy; (Delgado, Farinas, & Ruano, 2002) for Spain; (Aw, Chung, & Roberts, 2000; Liu, Tsou, & Hammitt, 1999; Roberts & Tybout, 1997) for Taiwan; (Clerides, Lach, & Tybout, 1998) for Colombia, Mexico and Morocco; (Isgut, 2001; Roberts & Tybout, 1997) for Columbia; (Poddar, 2004) for India; (V. H. Vu, 2012) for Vietnam; (Sinani & Hobdari, 2010) for Estonia found corroborate evidence of self-selection, but failed to find any evidence supporting learning by exporting. The above empirical studies confirm that exporting firms are more productive than non-exporting firms and revealed that higher productivity of firms occurs before entry into export markets. While some other studies have found no significant effect regarding the causality from firm productivity to the decision to export ((A. B. Bernard & Jensen, 2004) for the U.S.; and (Aw et al., 2000) in Korea).

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Similarly, a mixed picture also appears regarding empirical findings of the learning by exporting hypothesis in both developed and developing countries, albeit, feeble and less in number (see (Wagner, 2007a)). For example, using UK data, (Crespi, Criscuolo, & Haskel, 2008; Girma, Greenaway, & Kneller, 2003; Greenaway & Kneller, 2004, 2007) have found that firms boost their productivity advantage after being exporters. Similar results also found from Canada and Slovenia manufacturing plants by J. R. Baldwin and Gu (2003) and De Loecker (2007) respectively. In contrary to developed countries, in which evidence for learning effect is rare, in the developing countries learning by exporting effects is more popular. For instance, (Kraay, 1999; Park, Yang, Shi, & Jiang, 2010) for Chinese firms; (Blalock & Gertler, 2004) for Indonesian firms; (Yasar, Nelson, & Rejesus, 2006) for Turkey and (Bigsten et al., 2004) for Sub-Saharan African countries have found evidence of a post-exporting productivity gain. On the other hand, a number of studies have found no proof of the learning by exporting effect, even for major exporting countries (for instance: (Hailu & Tanaka, 2015) (A. B. Bernard & Jensen, 1999c; Hung, Salomon, & Sowerby, 2004) for the USA; (Fu, 2005) for China; (V. H. Vu, 2012) for Vietnam; (Arnold & Hussinger, 2005; Wagner, 2002) for Germany).


However, some studies have found evidence of coexistence of both hypotheses: for instance; (Aw, Roberts, & Winston, 2007) for Taiwan; (Alvarez & Lopez, 2005) for Chile; (Kimura & Kiyota, 2006) for Japan; (Girma, Greenaway, & Kneller, 2004; Greenaway & Kneller, 2004) for the UK; (Hahn, 2005) for Korea; (Fernandes & Isgut, 2005) for Colombia; (Bigsten et al., 2004) as well as (Van Biesebroeck, 2005) for SSA Countries; and (Bigsten & Gebreeyesus, 2009) for Ethiopia. Some other studies, while, have failed to find any evidence for either hypothesis and conclude that the performance characteristics of exporters and non-exporters are remarkably similar (e.g., (Girma et al., 2003); (Kim, Gopinath, & Kim, 2009) and (Sharma & Mishra, 2011) using data from Swedish, Korean, and Indian firms, respectively).


While trying to explain the reason behind the observed blended results across countries and time of the export and productivity nexus, the empirical literature has recently moved toward other aspects of firm heterogeneity. This includes international trade associated with the macroeconomic environment; the degree of competition and entry costs in the export markets that firms are likely to face. Some other studies also consider particular behavior of firms involved in international activities for the existence of a mixed result, for example, product and country diversification ((Andersson, 2001) for Sweden and (Wagner, 2007b) for Germany); import behavior ((Castellani, Serti, & Tomasi, 2010) for Italy); Geo-economic orientation ((Damijan, Polanec, & Prašnikar, 2004) for Slovenia) and FDI behavior ((Helpman, Melitz, & Stephen, 2004) for USA). According to Blalock and Gertler (2004), firms in countries with poor technology and low productivity can get a better advantage from export participation and thus the level of economic development may be the other reason for contradictory results. It also asserts that the variation in geographical and economic conditions of countries may be the reason for the nexus (Wagner, 2007b). Lastly, Sharma and Mishra (2011) also indicate the differing conclusions may originate from using a wide variety of econometric methodologies and approaches for testing these two hypotheses.


Moreover, the nonexistence of a consistent measurement of productivity can be responsible for the uncertain and mixed result of export productivity linkage. Some previous studies often use the conventional technique for estimating Total Factor Productivity (TFP) such as the Solow residual method which defines TFP growth as the residual of output growth after the contribution of labor and capital inputs have been subtracted from total output growth. This approach depends on an established assumption which includes the form of the production function is known; all firms are working effectively with no space for any inefficiency; neutral technical change and have a constant return to scale, which means that TFP growth equal to technical progress growth. If these assumptions do not hold, TFP measurements will be biased (Arcelus & Arocena, 2000; T. Coelli, 1998). Some others also use labor productivity to stand for productivity, yet this index just represents a part of the picture of productivity and should be considered as one of the attributes of exporting manufacturing firms in the Ethiopian context. In a study in Ethiopia, while considering the relationship between export status and firm productivity, Bigsten and Gebreeyesus (2009) used three different measures of firm performance – TFP, labor productivity (Q/L) and unit labor cost (ULC) of different industries from 1996 to 2005 and found a support for both hypotheses. Nonetheless, the above study and these methodologies don’t permit the decomposition of TFP change into its components such as technical progress change, technical change and scale efficiency change ((S. C. Kumbhakar & Lovell, 2003)). Rather, most studies often consider productivity under a single umbrella of investigation that does not give due consideration regarding the different parts of productivity and the importance of their influence even if it helps to understand whether gains in productivity levels are achieved through the efficient use of inputs or through technological progress. This will constrain further study regarding the relationship between export participation and productivity with its decompositions just when an aggregated index for productivity is taken. The only exception in this regard is the study by Fu (2005) for China who utilized a random effects panel data model to test the effect of export status on productivity growth and its parts. Its decomposition into technical efficiency and technical progress is also made by using a frontier approach which is examined by employing the Malmquist index. But it still overlooks the contribution of export intensity on scale efficiency and used industry not firm-level data. Furthermore, V. H. Vu (2012) also examines the causality of exporting and firm productivity using a different sample retrieved from a survey of Vietnamese SME firms by decomposing TFP change into technical progress change, technical efficiency change, and scale efficiency. The study failed to find evidence in support of export participation on any of TFP components. However, their study based on the data surveyed, just for private small and medium firms and a short panel dataset which may not give a full picture of this relationship.


Despite there are many empirical studies using datasets from different countries to test the hypothesis, it seems at an informative stage and were no superior explanation exists (Sharma & Mishra, 2011). Besides, the above issues bring up a question about whether the measurement of productivity can offer an alternative explanation for the mixed results in the relationship between productivity and export. Thus, the present study motivated by the existing empirical research crevice and the need to revisit the validity of the two hypotheses within manufacturing firms in Ethiopian context for the period 2000-2011. We measure productivity change by using Stochastic Frontier Approach (SFA) to release the assumption of a full efficiency of firms and decompose into its components, such as technical change, scale change and technological progress change by following S. Kumbhakar and Lovell (1998). Although other approaches like data envelopment analysis (DEA) may divide productivity change, the SFA has been preferred in this study. This is due to its advantages with regard to controlling with inefficiencies resulted from omitted variables, measurement errors, outliers and stochastic noise, which may result in a possible upward bias of inefficiency scores (Del Gatto, Di Liberto, & Petraglia, 2011). Besides, we used two additional productivity measures which are Levinsohn and Petrin (2003) methodology and labor productivity calculated by output per total employees, to test the robustness of the results. We then used different econometric methods to deal with the causality between export participation and productivity change with its compositions.


The paper has two main novelties vis?à?vis previous literature in the area of heterogeneous-firm trade empirical literature: first, in relation to decomposing productivity, to the best of my knowledge, it is the first investigation to consider the impact of export participation on each component of TFP in the context of African firms. Second, decomposing TFP can provide another way to explain the mixed findings in empirical studies as well as provides additional insights into understanding the recent debate on TFP growth. In sum, it will broaden our empirical insight into what policies and strategies should be pursued to improve productivity and thus their competitiveness in the global market in line with each component. Our contention is that export participation can adversely affect productivity change, but it may create favorable effects on each component of productivity change. Thus, considering TFP as an aggregated index will conceal such fascinating points. Furthermore, we complement the evidence by studying the impact of other firm-specific characteristics as determinants of its export performance. Finally, Ethiopia makes for a particularly interesting study in light of two main reasons: its’ relatively strong export-oriented policy and the absence of such empirical analysis.


The remainder of the paper is organized as follows. Section 2 presents some background information about Ethiopian economy. Data sources are presented in section 3 while section 4 specifies the empirical models. Finally, section 5 and 6 consecutively discusses the results and concluding remarks.

1 Meaning that both effects can sequentially play a role, before and after firms start exporting

2 such as transport costs, modification costs to meet foreign tastes and regulations, distribution or marketing costs and setup costs to establish distribution network which prevent less productive firms from entering foreign markets.