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Food safety regulations and fish trade: Evidence from European Union-Africa trade relations
Journal of Commodity Markets ∎ (∎∎∎∎) ∎∎∎–∎∎∎
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Food safety regulations and fish trade: Evidence from European Union-Africa trade relations Olayinka Idowu Kareem Georg Forster Research Fellow, Cooperation and Development Research Group, Marburg Centre for Institutional Economics, University of Marburg, Marburg, Germany
a r t i c l e i n f o
abstract
Article history: Received 2 September 2015 Received in revised form 5 July 2016 Accepted 6 July 2016
The preponderance of food regulations in international trade and the stringency in standards application has trade effects for Africa. The proliferation of preferential tariffs among trading partners has brought to fore the importance and increasing use of technical regulations in global trade. These regulations have their pros and cons for different economic agents. To this end, this study investigated the export effects of the EU fish standard regulations for Africa in a two-step Helpman et al. (2008) model. The study covers 52 African countries from 1995 to 2012. It finds that, fish standards are trade enhancing at the extensive margins, but not the case at the intensive margins. Thus, the quality standards' institutions must be strengthened in Africa through adequate development of science and technology in order accelerate export intensity. & 2016 Elsevier B.V. All rights reserved.
JEL classification: C33 C87 F13 F42 Keywords: Food regulations Fish trade EU-Africa Gravity model
1. Introduction International trade has been linked with economic growth, such that countries' participation proffers the opportunity of integrating and interacting with the rest of the world. Global integration of countries, especially the poorer ones, provides the avenue for sustainable growth and reduction in poverty. Thus, trade flows have the potentials of improving foreign earnings, sustainable growth and unemployment reduction. In practice, however, is often not the case as there are various barriers to trade, especially in the commodities that developing countries and particularly Africa have comparative advantage. Due to these trade policies, Africa found it difficult to take full E-mail addresses: [email protected], [email protected]
advantage of the opportunities embedded in global trade. The continuous trade negotiations and agreements among countries have led to substantial reduction in the impact of tariffs on global trade. This is because recent evidences have shown that tariffs are collapsing in which brought to prominence the relevance and the preponderance of the use of non-tariff measure (NTMs) in regulating international trade (Fugazza, 2013; WTO, 2012). Nicita and Gourdon (2013) used a broad definition of NTMs to present a frequency index that shows that among the NTMs, technical measures are most often used. Out of these technical measures, the product standards stand out due to its ability to be used for trade protectionism and/or the enhancement of the flow of trade through food safety standards that meet the changing taste and preferences of consumers. This study deals with public product standards, which are mandatory and must be adhere and/or comply with before market access can be guarantee, while
http://dx.doi.org/10.1016/j.jcomm.2016.07.002 2405-8513/& 2016 Elsevier B.V. All rights reserved.
Please cite this article as: Kareem, O.I., Food safety regulations and fish trade: Evidence from European Union-Africa trade relations. Journal of Commodity Markets (2016), http://dx.doi.org/10.1016/j.jcomm.2016.07.002i
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private standards, other form of standards, are not mandatory (voluntary) such that their compliance are voluntary but could be required at the border before market access.1 To many least developed countries (LDC) and developing countries, standard requirements2 (SPS) are trade restrictive such that it's added to the series of costs faced by their exporters, particularly in the developed markets. Moise and Le Bris (2013) argued that the NTMs can almost double the trade barriers effects imposed by tariffs for some products. Besides, there are increasing incidences of technical barrier to trade (TBT) and Sanitary and Phytosanitary measures (SPS) that pose concern for developing countries' exports (Fugazza, 2013). Furthermore, he posits that on the average, about 30% of products lines are confronted with TBT, while that of SPS is 15% of trade in countries, especially the developed ones. This has implication for developing countries' export earnings, income and their quest for sustainable development through reduction in poverty, unemployment and smallholder producers' inclusiveness in the trajectory of development. The quest for sustainable development among other factors is the reason for Africa's continuous global integration, especially through trade relations. Kaplinsky (2008) has identified trade among other channels3 with which countries could integrate into the global market. Trade channel of global integration has been explored by African countries, however, the gains from trade as advocated by orthodox trade theories have not been fully realized due to the quality of the exports, export base and their development stages as well as the protectionism nature of standards. Many empirical studies (see Chemnitz et al., 2007; Otsuki et al., 2001) have shown that standards are trade restrictive as being used. However, studies such as Henson and Humphrey (2008) and Maertens and Swinnen (2009) conclude that, standard requirements due to change in taste and preferences will enable exporters to engage in product upgrading. Although, in the short run, the exporters might incur some compliance costs, but in the long run, these costs will stabilize and thereby enhance their exports to these markets. It should be noted that, there are many food safety standards before a product could access any given market. However, majority of the studies in this area often used single standard requirement. For instance, Liu and Yue (2011) used the Hazard Analysis Critical Control Point (HACCP) on EU orange trade. Otsuki et al. (2001) quantified the impact of EU aflatoxins on African exports of cereals, dried fruits and nuts. Yua Yang and Findlay (2008) investigates the effects of the maximum residue limit (MRL) standards on China's exports of vegetables (Chlorpyrifos MRL) and aquatic products (Oxytetracycline MRL). Wei et al. (2012) used MRL of pesticides on China's tea export. Xiong and Beghin (2011) used the tightening of the EU maximum residue limit 1 Please, see Kareem (2014) for further reading on the conceptual issues in standard requirements. 2 The type of standards is public standards, which is mandatory and different from the private standards that voluntary. 3 Other channels are investment, migration, finance, global governance and environment.
(MRL) on aflatoxins in 2002 on Africa's export of groundnut, etc. Contrarily, this study departs from these previous studies by considering all the applicable standards for the selected commodity. All the applicable standards are standard requirements set by the EU to guide and/or regulate the content of this commodity, which for fish as at the end of 2013, are 10 requirements4. Also, the use of mostly unexplored Perinorm standards data in the twostage Helpman et al. (2008) model, are very scarce in the literature, especially those with African trade data. Although, in every product, certain standard might be dominant5 among the requirements, but all the standard requirements must be complied with before accessing the market. To this end, this study inquires the following; do the EU fish standard requirements affect Africa's exports? Thus, from this research question, this study draws its objective, which is to investigate the impact of EU's fish standard regulations on Africa's exports in a Helpman et al. (2008) gravity model.
2. Material and methods The issue of technical standards and Africa's exports is vital to the continent's development aspiration. Its importance has been emphasized and investigated by early empirical studies, such as Otsuki et al. (2001), Okello and Roy (2007) and Maertens and Swinnen (2009). However, in spite of this issue to Africa, only scanty empirical studies exist. The paucity of empirical studies which was acknowledged by Shepherd and Wilson (2010) has inhibited research and evidence-based policy formulation by African governments in order to solve the problem of inadequate conformity and thereby inaccessibility of African exports to the markets of its trading partners (Kareem, 2016). Only of recent that efforts are being made to mitigate the problem of aflatoxins in some commodities, but product standards go beyond this single requirement of mycotoxins. Three strands of trade impact of standards are available in the literature: first, those that concluded that standards are trade inhibiting; second, studies that found standards are trade enhancing; and finally, some studies argued the fact that standards could be trade inhibiting (in the short run) and enhancing (in the long run). Studies conducted by Chemnitz et al. (2007), Wilson and Abiola (2003), Czubala et al. (2009), Otsuki et al. (2001) etcetera, show that Africa's exports were restricted to the developed markets due to its inability to meet the standards set by these markets. For instance, Mutume (2006) argued that the implicit standards that are aimed at raising African countries' standards to the developed countries' levels resulted in extra layers of developed countries regulatory barriers, which has shut out cheap exports from Africa. Furthermore, there are studies such as Ignacio (2008), Jaffee and Henson (2004), Henson and Jaffee (2008), 4 These range from Microbiological contaminants, Veterinary drug residues, Heavy metals, Product composition to Biotoxins/Contaminants (see Kareem (2011)). 5 For instance, aflatoxin in groundnut, cereal and other products.
Please cite this article as: Kareem, O.I., Food safety regulations and fish trade: Evidence from European Union-Africa trade relations. Journal of Commodity Markets (2016), http://dx.doi.org/10.1016/j.jcomm.2016.07.002i
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Henson and Humphrey (2008), Maertens and Swinnen (2009), etc., which conclude that standards could serve as impetus for long run export growth in the agricultural and food sector. They are of the view that standards could act as a bridge between producers in Africa and consumer preferences in developed markets, which can serve as catalyst for improving, upgrading and modernizing food supply system in the continent that would enhance their competitive capacity. Put differently, Foletti and Shingal (2014), McCullough et al. (2008), Swinnen (2007), Henson (2006), Ferro et al. (2015), Kareem (2014) show that the trade impact of standards could be both restrictive and enhancing depending on the degree of adjustment of institutions regulating trade. Their conclusions indicate that the rise in standards, both private and public, has led to sudden change in the organization of exports, especially food exports and thereby have effects on distribution of welfare not only across countries but also along supply chains and among rural dwellers (World Bank, 2005; Beghin et al., 2015). The research findings of these studies are mainly influenced by the type of standards that were covered (see Murina and Nicita (2014), Henson (2006), Henson and Northen (1998), Henson and Reardon (2005), Anders and Caswell (2009), Disdier et al. (2008), Xiong and Beghin (2014), and Moenius (2007), etc). A meeting point in all these empirical studies relating to the effects of standards on the economies of Africa is that the measures would have its adverse effects on the continent's exports at the initial stage. However, the subsequent impact would depend on the transformation level that must have taken place in the quality of agricultural output due to standardization requirements at the trade partners' markets. Therefore, a perusal of the literature on public standards shows that there are different indicators that have been used to measure standards (see Otsuki et al. (2001), Yua Yang and Findlay (2008), Xiong and Beghin (2011), 2014, Ferro et al. (2013), Mangelsdorf (2011), and Li and Beghin (2014)). The convergence of all these studies that have used one measure of standards is that their conclusions are based on the fact that those measures of standards that they have used were the ones that impacted on the market access of the selected export products.6 However, none of these studies have clearly shown that their selected commodities had other applicable standard requirements beyond the focused standards. Most often the explanation these studies give is that the indicator (s) that they have used are the most relevant applied product standards to the export items (see Fugazza (2013), Shepherd and Wilson (2013), Czubala et al. (2009), Ferro et al. (2015)). Contrary, UNIDO (2010) and RASFF (2013) have shown that all the applied standards are equally relevant and important that require compliance, of which noncompliance will lead to border rejection of the products. To this end, it could be seen that using one or two measures of public standards from all the applicable product standards will lead to selection bias, while the 6 That is, their inferences on market access for the selected products were based on the chosen standards, i.e. aflatoxin, pesticides, etc.
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conclusions drawn would be unreliable and misleading. At best, what ought to be done by these studies is to make their inferences and deductions with respect to the impact of the chosen product standards on the selected products and not on the market access of the products since other applied standards to the product are not considered.7 The generalization of the impact of one product standard on market access of such product would be misleading and will not give us efficient information.8 However, this study has documented the trend and stock of the time series of the applied product standards in the EU for some agricultural food products. This study uses the Perinorm dataset9 to document this time series of standards data. This database was also explored by Blind and Jungmittag (2005), Mangelsdorf (2011), Czubala et al. (2009), Shepherd and Wilson (2013). It should be noted that Shepherd and Wilson (2013) used voluntary product standards that are applicable to food and agriculture in the EU market, while Czubala et al. (2009) used the EU harmonized voluntary standards that aligned with the International Standard Organisation (CEN-European Committee for Standardization) for textiles and clothing (manufacturing) goods from Africa, which is different from the EU directives that this study used. The EU directives are the mandatory standards. Mangelsdorf (2011) used both EU and China voluntary standards for 36 technological fields. Similarly, Blind and Jungmittag (2005) examine the effects of technical standards on technological innovation and patent right for Germany and trade between Germany and UK. I have used all the applicable standards to each of the selected agriculture food exports to the EU as were reported by this source.
3. Theory/calculation/empirical strategy In order to investigate the fish exports' effects of product standards in the trade relation between Africa and the EU, I adapted the two – stage Helpman et al. (2008, hereafter called HMR) model. It is important to note that it was Heckman (1979) that first developed a model that correct for sample selection bias and specification error with nonrandom zero trade. However, a new dimension was brought to the Heckman model with the contribution of Helpman et al. (2008) when they argued that there will be estimation bias whenever only positive trade flows are considered in trade relations without considering countries that do not trade due to the fact that vital information in data must have been lost. They also opined that there is symmetry in standard gravity model specifications, which is inconsistent with the data and thereby, bias the estimation there-from. Thus, HMR model corrects these biases by developing a theory with positive and zero trade flows among trading countries, while also deriving estimation procedures that make use of available information in the 7 Also, an explicit assumption ought to be made that other applied standards are held constant. 8 Fallacy of hasten generalization. 9 Perinorm has the most reliable and comprehensive standards database for the EU.
Please cite this article as: Kareem, O.I., Food safety regulations and fish trade: Evidence from European Union-Africa trade relations. Journal of Commodity Markets (2016), http://dx.doi.org/10.1016/j.jcomm.2016.07.002i
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dataset of trading and non-trading countries. Building on Anderson and van Wincoop (2003) gravity model, HMR developed an estimable trade effect of trade barriers at the extensive and intensive margins of trade in line with Melitz (2003) model. HMR model shows the heterogeneity of firms in the industry, while arguing that any model of firm level export effects of trade barriers without consideration for the heterogeneity of firm and zero trade would be liable to selection bias. The inclusion of firm level heterogeneity in the correction of sample selection distinguishes HMR model from Heckman model. Hence, the importance of the model in determining the extensive and intensive margins of trade has been emphasized in recent studies (see Ferro et al. (2013), Munasib and Roy (2013), Crivelli and Groschl (2012), and Helpman et al. (2008)). I would make use of mostly unexploited standards data from the Perinorm database. Specifically, this study shall test the null hypothesis that the EU standards are trade impeding to Africa's fish exports. Fish standards/regulations will have effects on trade and in this case export from Africa. The reason behind the choice of fish is that, Africa produced it abundantly but given the standard requirements (trade policy in the import market), conditions of the producers and the level of development on the continent, it cannot export much of them. Thus, Africa has the potentials of increasing the outputs of fish for export in the future. So, the extensive margin shows the possibility or probability of market access to potential exporters and disappearing exporters, that is, the probability of trading in the future given the standard requirements. Thus, to test this hypothesis, a Helpman et al. (2008) gravity model is specified as follows:
Tijt = β1 + Cij ϑ + πEijt + αSTDtjt + εijt
(1)
Vijt = β2 + γit + ρjt + πSTDtjt + Cij ϑ + φσij + τij + εijt
(2)
Where Tijt is a binary variable that equals 1 if the export from country i to j at time t is nonzero, otherwise it is 0, and Vijt is the export value from country i to j at time t. The intercept are β1 and β2; the importer and exporter fixed effects are γit and ρjt , respectively; Cij is a vector of pair – varying control variables such as distance, language, colonial affiliation, regional trade agreement (RTA) and others included. Eijt is the exclusion variable that does not enter the second – stage regression; τij is the unobserved firm heterogeneity - the number of firms exporting from country i to j, which can possibly be zero; and σij is the inverse mills ratio from the first stage regression. Standards in the equation are the STDtjt ; which are the EU harmonized standards. This study uses common language as the exclusion variable in the model, although HMR used common religion but acknowledged that common language and colonial affiliation can also serve same purpose. The robust cluster errors have been corrected in the first-step estimation that often arises in this type of model. The multilateral trade resistance variables were included in the estimation of intensive margins of export but not reported in the table due to the large size of the cross-sections; however, they were not estimated in the extensive
margins due to the incidental parameter problems (see Neyman and Scott (1948)) that often arise when estimating fixed effects coefficients in a probit model when the time (t) is small. I have estimated the extensive model using the probit regression since the dependent variable in the model is binary. This estimation corrects the robust cluster errors and distils the inverse mills ratio from the first-step regression, which was used in the second-step regression (intensive margins estimation) as an explanatory in order to correct any selection bias that can be induced by the firms' heterogeneity. The second-step equation was estimated with the nonlinear least square regression as required by the HMR technique. 3.1. The data Perinorm database provided the product standards data, which is more comprehensive and current than the UNCTAD Trade Analysis Information System (TRAINS) NTMs data in the World Integrated Trade Solution (WITS) database. UNCTAD acknowledged the fact that the NTMs dataset in WITS is limited in coverage, updatedness and data quality, country and data coverage.10 This study uses the food safety regulations that are the EU directives on fish, which are legislations that must be compliance with otherwise market access will be denied. A directive of the EU is said to be in force in a particular year when it is published in that year or published prior to the year considered, but still in existence or has not been withdrawn. Drafts standards are excluded from the dataset, while amendments to existing standards are treated as additional standards. I have matched the cumulative standards in each year to the appropriate HS 1998 classification. Perinorm also has other standards data such as private standards like the International Standard Organisation and voluntary standards such as European Committee for Standardization (CEN–EN). Other trade data were sourced from the World Integrated Trade Solution (WITS) database. The control variables such as the gross domestic products (GDPs) were from the World Development Indicators (WDI). This study shall cover the period from 1995 to 2012 for 52 African countries as exporters in all the estimations. The period covered in this study has EU 27 as the importing countries. Inclusion of EU countries in the dataset is based on their year of accession to the organization. For instance, for 1995, 15 countries are included, and the number later increases to 25 in 2004 and 27 from 2007 to 2012. The technical regulation vis a vis, food safety standards were directives on rules, regulations and laws governing the content requirements, which were transformed into the statistics of occurrence and/or incidences. Cumulative standards data were used with the deduction of any withdrawal and addition of new regulations.11 I have the 10 See www.unctad.info/fr/Trade-Analysis-Branch/Key-Areas/NonTariff-Measures/ 11 That is, in 1995 if there are 2 regulations for a product and in 1996, another 2 is added, then I added them together to give total regulations for the product as 4. And if by the following year, which is 1997 no addition to the regulation but a withdrawal of a regulation previously in
Please cite this article as: Kareem, O.I., Food safety regulations and fish trade: Evidence from European Union-Africa trade relations. Journal of Commodity Markets (2016), http://dx.doi.org/10.1016/j.jcomm.2016.07.002i
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following simple formulae for the calculation of the cumulative standards:
Zt −1 + ρt − ωt
(3)
Where Zt − 1 is the previous cumulative number of standards, ρt stands for the number of additional standards in time t, while the number of standards withdrawn in time t is represented by ωt . The formula is applicable from the second year. This study selected a high-value commodity; fish. The data for fish were obtained from WITS at the HS-6-digit level. The economic size or mass variables are the GDPs (as enunciated in any standard gravity model and amplified by Baldwin and Taglioni (2007)) of the importing and exporting countries that are obtained from the WDI.
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Table 1 Extensive and Intensive Margins of Exports Results. Variable
Extensive Margin
Intensive Margin
Exporter GDP
0.2940*** (0.0494) 0.6524*** (0.0547) 0.1463*** (0.0328) 0.0018 (0.2298) 0.1060 (0.2048) 0.0124*** (0.0030) 0.5341*** (0.2084)
0.9832*** (0.1678) 0.4703*** (0.2148) 2.8467*** (2.0021) 2.0975*** (0.2653) 0.0487 (0.1640) 0.0171*** (0.0047)
Importer GDP EU Standard Distance RTA Price Language Inverse Mills
4. Results Constant
The results of the two-step HMR model are present in this section. The extensive and intensive margins of trade results are together in Table 1. 4.1. Extensive and intensive margins of export Table 1 presents the empirical results of the selected commodity, vis a vis, fish at both the extensive and intensive margins. The economic mass of the trading partners (exporters and importers' GDPs) propel the probability of exporting African fish to the EU. There is increased probability of exporting fish by new exporters, those that have exported in the past but are no longer exporting (disappearing exporters) and would want to export in the future as well as those that are currently exporting with the probability of expanding their exports for every economic growth witnessed. It could be seen that economic growth in the exporting countries enhances the possibility of new firm entry into exporting of fish such that a percentage increase in GDP would raise the probability of new exporters, disappearing exporters and existing exporters of fish export to the EU by 0.29%. Similarly, the expenditure on Africa's fish, measured by the GDPs of importing countries, shows that this commodity is normal good such that an additional percentage increase in expenditure on this commodity enhances the probability of exporting by 0.65%. The EU standards on fish significantly did not hinder the extensive margins of exporting fish, which means that the standards were not restrictive to the fact that they will prevent export of fish at the extensive margin. This implies that many of the exporters at this margin of trade often beforehand consider the standard requirements for market access and they ensure adequate compliance prior entering the market, which is in conformity with Maertens and Swinnen (2009), Mangelsdorf et al., 2012, Xiong and Beghin (2011), Liu and Yue (2011), Reyes (2011), Jaffee and Henson (2004), Henson and Humphrey (2009) and Henson and Jaffee (2008). More so, (footnote continued) existence, then for the year the total regulation for the product is 3 and so on.
Wald Chi-sq Adjusted R-square Observation Exporter Fixed Effects Importer Fixed Effects
22.8174*** (3.0708) 291.81 (0.0000) 7650 No No
0.8708 (0.1878) 14.4764*** (4.2196)
0.6291 2848 Yes Yes
Source: Estimated. Note: All variables are in log form except the dummy variables. The equations at the extensive margin were estimated without the multilateral trade resistance variables due to the incidental parameter problem. *, ** and *** denote significant level at 10%, 5% and 1%, respectively. Figures in parentheses are the robust standards errors.
some importers have assisted many of their exporters and potential exporters technologically in order to comply with the technical regulations, which is in line with the thought and findings of Okello and Roy (2007). The trade costs proxy by distance does not inhibit export of fish at this margin of trade, while the regional trade agreements did not significantly propel trade. However, common language and price are significant factors to consider at the extensive margins of export. Inverse relationship exists between the export price and extensive margins of fish export, while language is directly related to it. (Table 2). The estimates of the intensive margin of exports are also presented in Table 1, where it could be seen that Africa's income growth has not translated into increased export of fish. This implies that the promotion of fish export from the growth being experience by Africa has been discouraging such that, as more income is accruing, there is neglect of expanding export of fish at the intensive margin of trade despite the demand for the commodity in the EU. Xiong and Beghin (2011) conclude that the trade potential of African exporters is more constrained by domestic supply issue rather than the limited market access. The absorptive capacity of this commodity in the EU is relatively encouraging, which depicts the fact that there is demand for this commodity. In other words, the expenditure on Africa fish in this market are very encouraging if only supply of the commodity could be expanded and improved upon. This is as a result of the compliance to the EU standards in which the product quality meets the taste in this market at the extensive margins. To this end, the EU standards at the intensive margins of fish export are insignificant, though with
Please cite this article as: Kareem, O.I., Food safety regulations and fish trade: Evidence from European Union-Africa trade relations. Journal of Commodity Markets (2016), http://dx.doi.org/10.1016/j.jcomm.2016.07.002i
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Table 2 Estimates of Robustness Check with Instrumental Variable Regression. Extensive Margin
Intensive Margins
Variable
IVR 1
IVR 2
Probit 1
Probit 2
IVR1
IVR2
FGLS 1
FGLS2
Exporter GDP
1.5e-15 (1.1e-15) 8.5e-16 (1.2e-15) 8.7e-17 (1.5e-15) 8.4e-15*** (2.6e-15) 9.9e-16 (5.1e-15) 7.6e-17 (9.4e-17) 2.4e-15 (3.2e-15)
3.1e-16 (9.1e-16) 2.4e-15** (1.1e-15) 3.4e-16 (1.3e-15) 5.2e-15** (2.3e-15) 3.3e-16 (4.5e-15) 9.7e-17 (8.1e-17) 9.9e-16 (2.8e-15) 8.5e-17 (6.1e-16)
0.10*** (0.02) 0.24*** (0.02) 0.05*** (0.01) 0.03 (0.07) 0.04 (0.06) 0.01*** (0.00) 0.22*** (0.08) 0.04*** (0.01)
17.15*** (7.96) 0.24*** (0.02) 17.10** (7.96) 0.04 (0.08) 0.04 (0.06) 0.01*** (0.00) 0.22*** (0.08) 0.04*** (0.01) 17.06** (7.96)
5.7e-17 (2.3e-15) 1.0e-14*** (2.6e-15) 2.2e-14 (2.1e-14) 1.9e-13*** (3.5e-14) 2.8e-15 (2.5e-15) 3.3e-17 (4.3e-17)
3.1e-14 (3.7e-14) 6.9e-14 (7.3e-14) 4.0e-15 (2.0e-14) 1.9e-14 (8.5e-14) 6.5e-16 (5.7e-14) 9.9e-16 (1.7e-15)
0.22*** (0.08) 0.04 (0.18) 0.07 (0.09) 0.28** (0.13) 0.50** (0.24) 0.04*** (0.01)
54.27 (47.76) 0.04 (0.18) 54.14 (47.77) 0.27** (0.13) 0.46** (0.24) 0.04*** (0.01)
1.5e-14 (1.7e-14)
0.09*** (0.04)
8.3e-16*** (6.4e-17) 2.1e-12*** (4.0e-13)
2.7e-13 (8.5e-13) 2.5e-13 (1.9e-12)
1.63*** (0.54) 3.53*** (6.83)
0.09*** (0.04) 54.07 (47.77) 1.63*** (0.54) 3.36 (6.83)
2848
2848
0.14 2848
0.13 2848
Importer GDP EU Standard Distance RTA Price Language Tariffs ExporterGDP*SPS Inverse Mills Ratio Constant
7.8e-14 (5.8e-14)
9.8e-14** (5.0e-14)
8.02*** (0.95) 260.08 (0.00)
7.93*** (0.95) 264.29 (0.00)
7650
7650
7650
7650
Wald Chi-sq Adj. R2 Observation
Source: Estimated. Note: All variables are in log form except the dummy variables. The equations were estimated without the multilateral trade resistance variables due to the incidental parameter problem. *, ** and *** denote significant level at 10%, 5% and 1%, respectively. Figures in parentheses are the robust standards errors. IVR 1s are the instrumental variable regressions for the estimates in Table 1, while IVR 2s are the instrumental regressions for the new regressions with tariffs. Probit 1 and FGLS 1 are the estimations of probit and FGLS regressions as in Table 1 with tariffs inclusion, while probit 2 and FGLS 2 are the estimations with exporter GDP and fish standards interaction.
negative sign, indicating that the compliance at the extensive margins has help trade at the intensive margins. This reason for this insignificant impact of these standards is due to the supports and assistance rendered by the EU importers (particularly through global good agricultural practice, GLOBALGAP) and United Nations Industrial Development Organisation (UNIDO) (2010) in complying with the standards. This is in tandem with Asfaw et al. (2007), Mangelsdorf et al. (2012), Xiong and Beghin (2011), Liu and Yue (2011) and Reyes (2011) conclusions. The trade costs associated with the flow of export of this commodity significantly affects the flow of trade, which probably might be due to bottlenecks in the trade facilitation. Regional trade agreements did not contribute meaningfully to enhancement of export of this commodity, while price is significantly not an economical inhibiting factor. The results show that the selection bias in the model has been adequately corrected going by the significant value of the inverse mills ratio. Thus, at the intensive margins of Africa's fish export to the EU, the economic mass variables, trade costs and price are the important and main determinants of the volume of export.
5. The Robustness Check In order to ascertain the robustness of the results in this
study, a robust check has been carried out with a different estimation technique and variable inclusion. The instrumental variable regression (IVR) is estimated at both margins of trade with and without tariffs in order to ascertain whether there is no problem of standards being endogenous; using the path dependence-reputation (previous year technical standard regulations) as an instrument. Besides, probit regressions with tariffs as well as exporter's GDP and standards interaction are estimated for both commodities. The results confirm the positions of UNCTAD (2013), Kareem (2010, 2011) that the magnitude of the impact of tariffs is indistinguishable from zero. Also, the magnitudes of the estimates of IVR are not plausible. Therefore, the IVR technique is rather not appropriate for this study's dataset, that is the issue of endogeneity does not arise, which is the reason for probit and nonlinear regressions in Helpmanet al. (2008) model.
6. Conclusion The issue of product standards in global trade among the non-tariff barriers is very vital to most countries, especially the developing ones and Africa in particular, where it compliance has been seen as the necessary condition in accessing importing markets. A review of previous studies suggests three strands of conclusions in the
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literature; first strand argues that food safety standards are trade restrictive, while the other opined that they are not but trade propelling, however, the last strand are of the view that it could either be trade enhancing or restrictive depending on the capacity and endowment of exporters, cost of compliance, stage of development in exporting countries and the choice of standards used in the empirical analysis. This study gives supports to the fact that the impact of standards on trade though is product-specific, differential effects are also observed at the margins of trade. Further, the generalization of conclusion on market access from analysis of a product and standard requirement is not appropriate. To this end, the empirical analysis in this study used all the applicable fish standard regulations in a HMR model. At the extensive margins of export, standards propel fish trade. At the intensive margins, standard requirements are impediments for free flow of fish to this market. Fish export intensity was not encouraged as Africa income increases. Therefore, this study concludes that the impact of fish standard regulations on export depends on the margin of trade because of the significant differences in the costs of compliance across the margins of trade, the size of firms or countries,12 access to development assistance and countries' specific commodity promotion interests (prioritized commodity). That is, the interest of each country in promoting existing exporters or expanding the number of exporting firms will impact on the technical food regulations compliance at each margin of trade. Hence, Africa must ensure adequate fish standard regulations compliance in this market in order to be able to access the market. This could be achieved through development in science and technology and partnership with relevant local and international institutions for support in order to have access to modern technologies and capacity building. Further, the regional agreements, especially the on-going economic partnership agreement should include negotiations on NTMs, specifically the food safety standards issue.
Appendix A See Table A1. Table A1 Summary statistics. Variable
Mean
Min.
Max.
Exporter GDP Importer GDP EU Standard Distance RTA Price Language Tariff Inverse Mills
1.50e þ10 6.90e þ 11 7.22 5705.28 0.06 106.36 0.14 0.27 0.69
1.35eþ 08 5.64e þ 09 5.00 375.72 0.00 90.25 0.00 0.00 0.42
2.61e þ11 2.90e þ 12 10.00 10486.70 1.00 126.33 1.00 12.75 1.35
Source: Computed.
12
See Helpman et al. (2008)
7
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Food safety regulations and fish trade: Evidence from European Union-Africa trade relations Olayinka Idowu Kareem Georg Forster Research Fellow, Cooperation and Development Research Group, Marburg Centre for Institutional Economics, University of Marburg, Marburg, Germany
a r t i c l e i n f o
abstract
Article history: Received 2 September 2015 Received in revised form 5 July 2016 Accepted 6 July 2016
The preponderance of food regulations in international trade and the stringency in standards application has trade effects for Africa. The proliferation of preferential tariffs among trading partners has brought to fore the importance and increasing use of technical regulations in global trade. These regulations have their pros and cons for different economic agents. To this end, this study investigated the export effects of the EU fish standard regulations for Africa in a two-step Helpman et al. (2008) model. The study covers 52 African countries from 1995 to 2012. It finds that, fish standards are trade enhancing at the extensive margins, but not the case at the intensive margins. Thus, the quality standards' institutions must be strengthened in Africa through adequate development of science and technology in order accelerate export intensity. & 2016 Elsevier B.V. All rights reserved.
JEL classification: C33 C87 F13 F42 Keywords: Food regulations Fish trade EU-Africa Gravity model
1. Introduction International trade has been linked with economic growth, such that countries' participation proffers the opportunity of integrating and interacting with the rest of the world. Global integration of countries, especially the poorer ones, provides the avenue for sustainable growth and reduction in poverty. Thus, trade flows have the potentials of improving foreign earnings, sustainable growth and unemployment reduction. In practice, however, is often not the case as there are various barriers to trade, especially in the commodities that developing countries and particularly Africa have comparative advantage. Due to these trade policies, Africa found it difficult to take full E-mail addresses: [email protected], [email protected]
advantage of the opportunities embedded in global trade. The continuous trade negotiations and agreements among countries have led to substantial reduction in the impact of tariffs on global trade. This is because recent evidences have shown that tariffs are collapsing in which brought to prominence the relevance and the preponderance of the use of non-tariff measure (NTMs) in regulating international trade (Fugazza, 2013; WTO, 2012). Nicita and Gourdon (2013) used a broad definition of NTMs to present a frequency index that shows that among the NTMs, technical measures are most often used. Out of these technical measures, the product standards stand out due to its ability to be used for trade protectionism and/or the enhancement of the flow of trade through food safety standards that meet the changing taste and preferences of consumers. This study deals with public product standards, which are mandatory and must be adhere and/or comply with before market access can be guarantee, while
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private standards, other form of standards, are not mandatory (voluntary) such that their compliance are voluntary but could be required at the border before market access.1 To many least developed countries (LDC) and developing countries, standard requirements2 (SPS) are trade restrictive such that it's added to the series of costs faced by their exporters, particularly in the developed markets. Moise and Le Bris (2013) argued that the NTMs can almost double the trade barriers effects imposed by tariffs for some products. Besides, there are increasing incidences of technical barrier to trade (TBT) and Sanitary and Phytosanitary measures (SPS) that pose concern for developing countries' exports (Fugazza, 2013). Furthermore, he posits that on the average, about 30% of products lines are confronted with TBT, while that of SPS is 15% of trade in countries, especially the developed ones. This has implication for developing countries' export earnings, income and their quest for sustainable development through reduction in poverty, unemployment and smallholder producers' inclusiveness in the trajectory of development. The quest for sustainable development among other factors is the reason for Africa's continuous global integration, especially through trade relations. Kaplinsky (2008) has identified trade among other channels3 with which countries could integrate into the global market. Trade channel of global integration has been explored by African countries, however, the gains from trade as advocated by orthodox trade theories have not been fully realized due to the quality of the exports, export base and their development stages as well as the protectionism nature of standards. Many empirical studies (see Chemnitz et al., 2007; Otsuki et al., 2001) have shown that standards are trade restrictive as being used. However, studies such as Henson and Humphrey (2008) and Maertens and Swinnen (2009) conclude that, standard requirements due to change in taste and preferences will enable exporters to engage in product upgrading. Although, in the short run, the exporters might incur some compliance costs, but in the long run, these costs will stabilize and thereby enhance their exports to these markets. It should be noted that, there are many food safety standards before a product could access any given market. However, majority of the studies in this area often used single standard requirement. For instance, Liu and Yue (2011) used the Hazard Analysis Critical Control Point (HACCP) on EU orange trade. Otsuki et al. (2001) quantified the impact of EU aflatoxins on African exports of cereals, dried fruits and nuts. Yua Yang and Findlay (2008) investigates the effects of the maximum residue limit (MRL) standards on China's exports of vegetables (Chlorpyrifos MRL) and aquatic products (Oxytetracycline MRL). Wei et al. (2012) used MRL of pesticides on China's tea export. Xiong and Beghin (2011) used the tightening of the EU maximum residue limit 1 Please, see Kareem (2014) for further reading on the conceptual issues in standard requirements. 2 The type of standards is public standards, which is mandatory and different from the private standards that voluntary. 3 Other channels are investment, migration, finance, global governance and environment.
(MRL) on aflatoxins in 2002 on Africa's export of groundnut, etc. Contrarily, this study departs from these previous studies by considering all the applicable standards for the selected commodity. All the applicable standards are standard requirements set by the EU to guide and/or regulate the content of this commodity, which for fish as at the end of 2013, are 10 requirements4. Also, the use of mostly unexplored Perinorm standards data in the twostage Helpman et al. (2008) model, are very scarce in the literature, especially those with African trade data. Although, in every product, certain standard might be dominant5 among the requirements, but all the standard requirements must be complied with before accessing the market. To this end, this study inquires the following; do the EU fish standard requirements affect Africa's exports? Thus, from this research question, this study draws its objective, which is to investigate the impact of EU's fish standard regulations on Africa's exports in a Helpman et al. (2008) gravity model.
2. Material and methods The issue of technical standards and Africa's exports is vital to the continent's development aspiration. Its importance has been emphasized and investigated by early empirical studies, such as Otsuki et al. (2001), Okello and Roy (2007) and Maertens and Swinnen (2009). However, in spite of this issue to Africa, only scanty empirical studies exist. The paucity of empirical studies which was acknowledged by Shepherd and Wilson (2010) has inhibited research and evidence-based policy formulation by African governments in order to solve the problem of inadequate conformity and thereby inaccessibility of African exports to the markets of its trading partners (Kareem, 2016). Only of recent that efforts are being made to mitigate the problem of aflatoxins in some commodities, but product standards go beyond this single requirement of mycotoxins. Three strands of trade impact of standards are available in the literature: first, those that concluded that standards are trade inhibiting; second, studies that found standards are trade enhancing; and finally, some studies argued the fact that standards could be trade inhibiting (in the short run) and enhancing (in the long run). Studies conducted by Chemnitz et al. (2007), Wilson and Abiola (2003), Czubala et al. (2009), Otsuki et al. (2001) etcetera, show that Africa's exports were restricted to the developed markets due to its inability to meet the standards set by these markets. For instance, Mutume (2006) argued that the implicit standards that are aimed at raising African countries' standards to the developed countries' levels resulted in extra layers of developed countries regulatory barriers, which has shut out cheap exports from Africa. Furthermore, there are studies such as Ignacio (2008), Jaffee and Henson (2004), Henson and Jaffee (2008), 4 These range from Microbiological contaminants, Veterinary drug residues, Heavy metals, Product composition to Biotoxins/Contaminants (see Kareem (2011)). 5 For instance, aflatoxin in groundnut, cereal and other products.
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Henson and Humphrey (2008), Maertens and Swinnen (2009), etc., which conclude that standards could serve as impetus for long run export growth in the agricultural and food sector. They are of the view that standards could act as a bridge between producers in Africa and consumer preferences in developed markets, which can serve as catalyst for improving, upgrading and modernizing food supply system in the continent that would enhance their competitive capacity. Put differently, Foletti and Shingal (2014), McCullough et al. (2008), Swinnen (2007), Henson (2006), Ferro et al. (2015), Kareem (2014) show that the trade impact of standards could be both restrictive and enhancing depending on the degree of adjustment of institutions regulating trade. Their conclusions indicate that the rise in standards, both private and public, has led to sudden change in the organization of exports, especially food exports and thereby have effects on distribution of welfare not only across countries but also along supply chains and among rural dwellers (World Bank, 2005; Beghin et al., 2015). The research findings of these studies are mainly influenced by the type of standards that were covered (see Murina and Nicita (2014), Henson (2006), Henson and Northen (1998), Henson and Reardon (2005), Anders and Caswell (2009), Disdier et al. (2008), Xiong and Beghin (2014), and Moenius (2007), etc). A meeting point in all these empirical studies relating to the effects of standards on the economies of Africa is that the measures would have its adverse effects on the continent's exports at the initial stage. However, the subsequent impact would depend on the transformation level that must have taken place in the quality of agricultural output due to standardization requirements at the trade partners' markets. Therefore, a perusal of the literature on public standards shows that there are different indicators that have been used to measure standards (see Otsuki et al. (2001), Yua Yang and Findlay (2008), Xiong and Beghin (2011), 2014, Ferro et al. (2013), Mangelsdorf (2011), and Li and Beghin (2014)). The convergence of all these studies that have used one measure of standards is that their conclusions are based on the fact that those measures of standards that they have used were the ones that impacted on the market access of the selected export products.6 However, none of these studies have clearly shown that their selected commodities had other applicable standard requirements beyond the focused standards. Most often the explanation these studies give is that the indicator (s) that they have used are the most relevant applied product standards to the export items (see Fugazza (2013), Shepherd and Wilson (2013), Czubala et al. (2009), Ferro et al. (2015)). Contrary, UNIDO (2010) and RASFF (2013) have shown that all the applied standards are equally relevant and important that require compliance, of which noncompliance will lead to border rejection of the products. To this end, it could be seen that using one or two measures of public standards from all the applicable product standards will lead to selection bias, while the 6 That is, their inferences on market access for the selected products were based on the chosen standards, i.e. aflatoxin, pesticides, etc.
3
conclusions drawn would be unreliable and misleading. At best, what ought to be done by these studies is to make their inferences and deductions with respect to the impact of the chosen product standards on the selected products and not on the market access of the products since other applied standards to the product are not considered.7 The generalization of the impact of one product standard on market access of such product would be misleading and will not give us efficient information.8 However, this study has documented the trend and stock of the time series of the applied product standards in the EU for some agricultural food products. This study uses the Perinorm dataset9 to document this time series of standards data. This database was also explored by Blind and Jungmittag (2005), Mangelsdorf (2011), Czubala et al. (2009), Shepherd and Wilson (2013). It should be noted that Shepherd and Wilson (2013) used voluntary product standards that are applicable to food and agriculture in the EU market, while Czubala et al. (2009) used the EU harmonized voluntary standards that aligned with the International Standard Organisation (CEN-European Committee for Standardization) for textiles and clothing (manufacturing) goods from Africa, which is different from the EU directives that this study used. The EU directives are the mandatory standards. Mangelsdorf (2011) used both EU and China voluntary standards for 36 technological fields. Similarly, Blind and Jungmittag (2005) examine the effects of technical standards on technological innovation and patent right for Germany and trade between Germany and UK. I have used all the applicable standards to each of the selected agriculture food exports to the EU as were reported by this source.
3. Theory/calculation/empirical strategy In order to investigate the fish exports' effects of product standards in the trade relation between Africa and the EU, I adapted the two – stage Helpman et al. (2008, hereafter called HMR) model. It is important to note that it was Heckman (1979) that first developed a model that correct for sample selection bias and specification error with nonrandom zero trade. However, a new dimension was brought to the Heckman model with the contribution of Helpman et al. (2008) when they argued that there will be estimation bias whenever only positive trade flows are considered in trade relations without considering countries that do not trade due to the fact that vital information in data must have been lost. They also opined that there is symmetry in standard gravity model specifications, which is inconsistent with the data and thereby, bias the estimation there-from. Thus, HMR model corrects these biases by developing a theory with positive and zero trade flows among trading countries, while also deriving estimation procedures that make use of available information in the 7 Also, an explicit assumption ought to be made that other applied standards are held constant. 8 Fallacy of hasten generalization. 9 Perinorm has the most reliable and comprehensive standards database for the EU.
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dataset of trading and non-trading countries. Building on Anderson and van Wincoop (2003) gravity model, HMR developed an estimable trade effect of trade barriers at the extensive and intensive margins of trade in line with Melitz (2003) model. HMR model shows the heterogeneity of firms in the industry, while arguing that any model of firm level export effects of trade barriers without consideration for the heterogeneity of firm and zero trade would be liable to selection bias. The inclusion of firm level heterogeneity in the correction of sample selection distinguishes HMR model from Heckman model. Hence, the importance of the model in determining the extensive and intensive margins of trade has been emphasized in recent studies (see Ferro et al. (2013), Munasib and Roy (2013), Crivelli and Groschl (2012), and Helpman et al. (2008)). I would make use of mostly unexploited standards data from the Perinorm database. Specifically, this study shall test the null hypothesis that the EU standards are trade impeding to Africa's fish exports. Fish standards/regulations will have effects on trade and in this case export from Africa. The reason behind the choice of fish is that, Africa produced it abundantly but given the standard requirements (trade policy in the import market), conditions of the producers and the level of development on the continent, it cannot export much of them. Thus, Africa has the potentials of increasing the outputs of fish for export in the future. So, the extensive margin shows the possibility or probability of market access to potential exporters and disappearing exporters, that is, the probability of trading in the future given the standard requirements. Thus, to test this hypothesis, a Helpman et al. (2008) gravity model is specified as follows:
Tijt = β1 + Cij ϑ + πEijt + αSTDtjt + εijt
(1)
Vijt = β2 + γit + ρjt + πSTDtjt + Cij ϑ + φσij + τij + εijt
(2)
Where Tijt is a binary variable that equals 1 if the export from country i to j at time t is nonzero, otherwise it is 0, and Vijt is the export value from country i to j at time t. The intercept are β1 and β2; the importer and exporter fixed effects are γit and ρjt , respectively; Cij is a vector of pair – varying control variables such as distance, language, colonial affiliation, regional trade agreement (RTA) and others included. Eijt is the exclusion variable that does not enter the second – stage regression; τij is the unobserved firm heterogeneity - the number of firms exporting from country i to j, which can possibly be zero; and σij is the inverse mills ratio from the first stage regression. Standards in the equation are the STDtjt ; which are the EU harmonized standards. This study uses common language as the exclusion variable in the model, although HMR used common religion but acknowledged that common language and colonial affiliation can also serve same purpose. The robust cluster errors have been corrected in the first-step estimation that often arises in this type of model. The multilateral trade resistance variables were included in the estimation of intensive margins of export but not reported in the table due to the large size of the cross-sections; however, they were not estimated in the extensive
margins due to the incidental parameter problems (see Neyman and Scott (1948)) that often arise when estimating fixed effects coefficients in a probit model when the time (t) is small. I have estimated the extensive model using the probit regression since the dependent variable in the model is binary. This estimation corrects the robust cluster errors and distils the inverse mills ratio from the first-step regression, which was used in the second-step regression (intensive margins estimation) as an explanatory in order to correct any selection bias that can be induced by the firms' heterogeneity. The second-step equation was estimated with the nonlinear least square regression as required by the HMR technique. 3.1. The data Perinorm database provided the product standards data, which is more comprehensive and current than the UNCTAD Trade Analysis Information System (TRAINS) NTMs data in the World Integrated Trade Solution (WITS) database. UNCTAD acknowledged the fact that the NTMs dataset in WITS is limited in coverage, updatedness and data quality, country and data coverage.10 This study uses the food safety regulations that are the EU directives on fish, which are legislations that must be compliance with otherwise market access will be denied. A directive of the EU is said to be in force in a particular year when it is published in that year or published prior to the year considered, but still in existence or has not been withdrawn. Drafts standards are excluded from the dataset, while amendments to existing standards are treated as additional standards. I have matched the cumulative standards in each year to the appropriate HS 1998 classification. Perinorm also has other standards data such as private standards like the International Standard Organisation and voluntary standards such as European Committee for Standardization (CEN–EN). Other trade data were sourced from the World Integrated Trade Solution (WITS) database. The control variables such as the gross domestic products (GDPs) were from the World Development Indicators (WDI). This study shall cover the period from 1995 to 2012 for 52 African countries as exporters in all the estimations. The period covered in this study has EU 27 as the importing countries. Inclusion of EU countries in the dataset is based on their year of accession to the organization. For instance, for 1995, 15 countries are included, and the number later increases to 25 in 2004 and 27 from 2007 to 2012. The technical regulation vis a vis, food safety standards were directives on rules, regulations and laws governing the content requirements, which were transformed into the statistics of occurrence and/or incidences. Cumulative standards data were used with the deduction of any withdrawal and addition of new regulations.11 I have the 10 See www.unctad.info/fr/Trade-Analysis-Branch/Key-Areas/NonTariff-Measures/ 11 That is, in 1995 if there are 2 regulations for a product and in 1996, another 2 is added, then I added them together to give total regulations for the product as 4. And if by the following year, which is 1997 no addition to the regulation but a withdrawal of a regulation previously in
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following simple formulae for the calculation of the cumulative standards:
Zt −1 + ρt − ωt
(3)
Where Zt − 1 is the previous cumulative number of standards, ρt stands for the number of additional standards in time t, while the number of standards withdrawn in time t is represented by ωt . The formula is applicable from the second year. This study selected a high-value commodity; fish. The data for fish were obtained from WITS at the HS-6-digit level. The economic size or mass variables are the GDPs (as enunciated in any standard gravity model and amplified by Baldwin and Taglioni (2007)) of the importing and exporting countries that are obtained from the WDI.
5
Table 1 Extensive and Intensive Margins of Exports Results. Variable
Extensive Margin
Intensive Margin
Exporter GDP
0.2940*** (0.0494) 0.6524*** (0.0547) 0.1463*** (0.0328) 0.0018 (0.2298) 0.1060 (0.2048) 0.0124*** (0.0030) 0.5341*** (0.2084)
0.9832*** (0.1678) 0.4703*** (0.2148) 2.8467*** (2.0021) 2.0975*** (0.2653) 0.0487 (0.1640) 0.0171*** (0.0047)
Importer GDP EU Standard Distance RTA Price Language Inverse Mills
4. Results Constant
The results of the two-step HMR model are present in this section. The extensive and intensive margins of trade results are together in Table 1. 4.1. Extensive and intensive margins of export Table 1 presents the empirical results of the selected commodity, vis a vis, fish at both the extensive and intensive margins. The economic mass of the trading partners (exporters and importers' GDPs) propel the probability of exporting African fish to the EU. There is increased probability of exporting fish by new exporters, those that have exported in the past but are no longer exporting (disappearing exporters) and would want to export in the future as well as those that are currently exporting with the probability of expanding their exports for every economic growth witnessed. It could be seen that economic growth in the exporting countries enhances the possibility of new firm entry into exporting of fish such that a percentage increase in GDP would raise the probability of new exporters, disappearing exporters and existing exporters of fish export to the EU by 0.29%. Similarly, the expenditure on Africa's fish, measured by the GDPs of importing countries, shows that this commodity is normal good such that an additional percentage increase in expenditure on this commodity enhances the probability of exporting by 0.65%. The EU standards on fish significantly did not hinder the extensive margins of exporting fish, which means that the standards were not restrictive to the fact that they will prevent export of fish at the extensive margin. This implies that many of the exporters at this margin of trade often beforehand consider the standard requirements for market access and they ensure adequate compliance prior entering the market, which is in conformity with Maertens and Swinnen (2009), Mangelsdorf et al., 2012, Xiong and Beghin (2011), Liu and Yue (2011), Reyes (2011), Jaffee and Henson (2004), Henson and Humphrey (2009) and Henson and Jaffee (2008). More so, (footnote continued) existence, then for the year the total regulation for the product is 3 and so on.
Wald Chi-sq Adjusted R-square Observation Exporter Fixed Effects Importer Fixed Effects
22.8174*** (3.0708) 291.81 (0.0000) 7650 No No
0.8708 (0.1878) 14.4764*** (4.2196)
0.6291 2848 Yes Yes
Source: Estimated. Note: All variables are in log form except the dummy variables. The equations at the extensive margin were estimated without the multilateral trade resistance variables due to the incidental parameter problem. *, ** and *** denote significant level at 10%, 5% and 1%, respectively. Figures in parentheses are the robust standards errors.
some importers have assisted many of their exporters and potential exporters technologically in order to comply with the technical regulations, which is in line with the thought and findings of Okello and Roy (2007). The trade costs proxy by distance does not inhibit export of fish at this margin of trade, while the regional trade agreements did not significantly propel trade. However, common language and price are significant factors to consider at the extensive margins of export. Inverse relationship exists between the export price and extensive margins of fish export, while language is directly related to it. (Table 2). The estimates of the intensive margin of exports are also presented in Table 1, where it could be seen that Africa's income growth has not translated into increased export of fish. This implies that the promotion of fish export from the growth being experience by Africa has been discouraging such that, as more income is accruing, there is neglect of expanding export of fish at the intensive margin of trade despite the demand for the commodity in the EU. Xiong and Beghin (2011) conclude that the trade potential of African exporters is more constrained by domestic supply issue rather than the limited market access. The absorptive capacity of this commodity in the EU is relatively encouraging, which depicts the fact that there is demand for this commodity. In other words, the expenditure on Africa fish in this market are very encouraging if only supply of the commodity could be expanded and improved upon. This is as a result of the compliance to the EU standards in which the product quality meets the taste in this market at the extensive margins. To this end, the EU standards at the intensive margins of fish export are insignificant, though with
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6
Table 2 Estimates of Robustness Check with Instrumental Variable Regression. Extensive Margin
Intensive Margins
Variable
IVR 1
IVR 2
Probit 1
Probit 2
IVR1
IVR2
FGLS 1
FGLS2
Exporter GDP
1.5e-15 (1.1e-15) 8.5e-16 (1.2e-15) 8.7e-17 (1.5e-15) 8.4e-15*** (2.6e-15) 9.9e-16 (5.1e-15) 7.6e-17 (9.4e-17) 2.4e-15 (3.2e-15)
3.1e-16 (9.1e-16) 2.4e-15** (1.1e-15) 3.4e-16 (1.3e-15) 5.2e-15** (2.3e-15) 3.3e-16 (4.5e-15) 9.7e-17 (8.1e-17) 9.9e-16 (2.8e-15) 8.5e-17 (6.1e-16)
0.10*** (0.02) 0.24*** (0.02) 0.05*** (0.01) 0.03 (0.07) 0.04 (0.06) 0.01*** (0.00) 0.22*** (0.08) 0.04*** (0.01)
17.15*** (7.96) 0.24*** (0.02) 17.10** (7.96) 0.04 (0.08) 0.04 (0.06) 0.01*** (0.00) 0.22*** (0.08) 0.04*** (0.01) 17.06** (7.96)
5.7e-17 (2.3e-15) 1.0e-14*** (2.6e-15) 2.2e-14 (2.1e-14) 1.9e-13*** (3.5e-14) 2.8e-15 (2.5e-15) 3.3e-17 (4.3e-17)
3.1e-14 (3.7e-14) 6.9e-14 (7.3e-14) 4.0e-15 (2.0e-14) 1.9e-14 (8.5e-14) 6.5e-16 (5.7e-14) 9.9e-16 (1.7e-15)
0.22*** (0.08) 0.04 (0.18) 0.07 (0.09) 0.28** (0.13) 0.50** (0.24) 0.04*** (0.01)
54.27 (47.76) 0.04 (0.18) 54.14 (47.77) 0.27** (0.13) 0.46** (0.24) 0.04*** (0.01)
1.5e-14 (1.7e-14)
0.09*** (0.04)
8.3e-16*** (6.4e-17) 2.1e-12*** (4.0e-13)
2.7e-13 (8.5e-13) 2.5e-13 (1.9e-12)
1.63*** (0.54) 3.53*** (6.83)
0.09*** (0.04) 54.07 (47.77) 1.63*** (0.54) 3.36 (6.83)
2848
2848
0.14 2848
0.13 2848
Importer GDP EU Standard Distance RTA Price Language Tariffs ExporterGDP*SPS Inverse Mills Ratio Constant
7.8e-14 (5.8e-14)
9.8e-14** (5.0e-14)
8.02*** (0.95) 260.08 (0.00)
7.93*** (0.95) 264.29 (0.00)
7650
7650
7650
7650
Wald Chi-sq Adj. R2 Observation
Source: Estimated. Note: All variables are in log form except the dummy variables. The equations were estimated without the multilateral trade resistance variables due to the incidental parameter problem. *, ** and *** denote significant level at 10%, 5% and 1%, respectively. Figures in parentheses are the robust standards errors. IVR 1s are the instrumental variable regressions for the estimates in Table 1, while IVR 2s are the instrumental regressions for the new regressions with tariffs. Probit 1 and FGLS 1 are the estimations of probit and FGLS regressions as in Table 1 with tariffs inclusion, while probit 2 and FGLS 2 are the estimations with exporter GDP and fish standards interaction.
negative sign, indicating that the compliance at the extensive margins has help trade at the intensive margins. This reason for this insignificant impact of these standards is due to the supports and assistance rendered by the EU importers (particularly through global good agricultural practice, GLOBALGAP) and United Nations Industrial Development Organisation (UNIDO) (2010) in complying with the standards. This is in tandem with Asfaw et al. (2007), Mangelsdorf et al. (2012), Xiong and Beghin (2011), Liu and Yue (2011) and Reyes (2011) conclusions. The trade costs associated with the flow of export of this commodity significantly affects the flow of trade, which probably might be due to bottlenecks in the trade facilitation. Regional trade agreements did not contribute meaningfully to enhancement of export of this commodity, while price is significantly not an economical inhibiting factor. The results show that the selection bias in the model has been adequately corrected going by the significant value of the inverse mills ratio. Thus, at the intensive margins of Africa's fish export to the EU, the economic mass variables, trade costs and price are the important and main determinants of the volume of export.
5. The Robustness Check In order to ascertain the robustness of the results in this
study, a robust check has been carried out with a different estimation technique and variable inclusion. The instrumental variable regression (IVR) is estimated at both margins of trade with and without tariffs in order to ascertain whether there is no problem of standards being endogenous; using the path dependence-reputation (previous year technical standard regulations) as an instrument. Besides, probit regressions with tariffs as well as exporter's GDP and standards interaction are estimated for both commodities. The results confirm the positions of UNCTAD (2013), Kareem (2010, 2011) that the magnitude of the impact of tariffs is indistinguishable from zero. Also, the magnitudes of the estimates of IVR are not plausible. Therefore, the IVR technique is rather not appropriate for this study's dataset, that is the issue of endogeneity does not arise, which is the reason for probit and nonlinear regressions in Helpmanet al. (2008) model.
6. Conclusion The issue of product standards in global trade among the non-tariff barriers is very vital to most countries, especially the developing ones and Africa in particular, where it compliance has been seen as the necessary condition in accessing importing markets. A review of previous studies suggests three strands of conclusions in the
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literature; first strand argues that food safety standards are trade restrictive, while the other opined that they are not but trade propelling, however, the last strand are of the view that it could either be trade enhancing or restrictive depending on the capacity and endowment of exporters, cost of compliance, stage of development in exporting countries and the choice of standards used in the empirical analysis. This study gives supports to the fact that the impact of standards on trade though is product-specific, differential effects are also observed at the margins of trade. Further, the generalization of conclusion on market access from analysis of a product and standard requirement is not appropriate. To this end, the empirical analysis in this study used all the applicable fish standard regulations in a HMR model. At the extensive margins of export, standards propel fish trade. At the intensive margins, standard requirements are impediments for free flow of fish to this market. Fish export intensity was not encouraged as Africa income increases. Therefore, this study concludes that the impact of fish standard regulations on export depends on the margin of trade because of the significant differences in the costs of compliance across the margins of trade, the size of firms or countries,12 access to development assistance and countries' specific commodity promotion interests (prioritized commodity). That is, the interest of each country in promoting existing exporters or expanding the number of exporting firms will impact on the technical food regulations compliance at each margin of trade. Hence, Africa must ensure adequate fish standard regulations compliance in this market in order to be able to access the market. This could be achieved through development in science and technology and partnership with relevant local and international institutions for support in order to have access to modern technologies and capacity building. Further, the regional agreements, especially the on-going economic partnership agreement should include negotiations on NTMs, specifically the food safety standards issue.
Appendix A See Table A1. Table A1 Summary statistics. Variable
Mean
Min.
Max.
Exporter GDP Importer GDP EU Standard Distance RTA Price Language Tariff Inverse Mills
1.50e þ10 6.90e þ 11 7.22 5705.28 0.06 106.36 0.14 0.27 0.69
1.35eþ 08 5.64e þ 09 5.00 375.72 0.00 90.25 0.00 0.00 0.42
2.61e þ11 2.90e þ 12 10.00 10486.70 1.00 126.33 1.00 12.75 1.35
Source: Computed.
12
See Helpman et al. (2008)
7
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