C ONCEPTO DE PEQUEÑA EMPRESA MANUFACTURERA

A production-consumption pairs approach is employed in this chapter in order to examine the contribution of preferential tariffs to the South Africa-Zambia border effect. The baseline production-consumption pair model is specified as follows:

𝑝𝑖,𝑐,𝑡= 𝛽0+ 𝛽1𝑝𝑖,𝑝,𝑡+ 𝛽2ln(𝑑𝑖𝑠𝑡𝑝𝑐) + 𝛽3ln(𝑑𝑖𝑠𝑡𝑝𝑐)²+ 𝛽4𝑏𝑜𝑟𝑑𝑒𝑟𝑆𝐴−𝑍𝑎𝑚

+ 𝛽5𝑏𝑜𝑟𝑑𝑒𝑟𝑆𝐴−𝑍𝑎𝑚∗ 𝑙𝑛(1 + 𝑝𝑡𝑎𝑟𝑖𝑓𝑓𝑍𝑎𝑚𝑆𝐴𝑖,𝑡) + 𝛽6ln (𝑛𝑜𝑛𝑡𝑟𝑎𝑑𝑒𝑑𝑝𝑟𝑖𝑐𝑒𝑐,𝑡) + 𝛾𝑡+ 𝛾𝑖+ 𝜀𝑝𝑐,𝑡 (2) where 𝑝_{𝑖,𝑐,𝑡} is the log price of product i in consumption district c at time t; 𝑝_{𝑖,𝑝,𝑡} is the log price of product i in the production location at time t; ln(𝑑𝑖𝑠𝑡_𝑝𝑐) is the log of the shortest road distance between the production location and consumption district c, and ln(𝑑𝑖𝑠𝑡_𝑝𝑐)² is log distance squared;⁷⁹ 𝑏𝑜𝑟𝑑𝑒𝑟_{𝑆𝐴−𝑍𝑎𝑚} is a dummy variable equal to one if consumption district c is located in Zambia and zero otherwise; 𝑝𝑡𝑎𝑟𝑖𝑓𝑓𝑍𝑎𝑚𝑆𝐴_𝑖,𝑡 is Zambia’s preferential tariff offer to South Africa for product i at time t; ln(𝑛𝑜𝑛𝑡𝑟𝑎𝑑𝑒𝑑𝑝𝑟𝑖𝑐𝑒_𝑐,𝑡) is the log dollar price of a men’s haircut in consumption district c at time t; 𝛾_𝑡 and 𝛾_𝑖 are time and product fixed effects, respectively; and 𝜀_{𝑝𝑐,𝑡} is the regression error term.

The application of the production-consumption pair model is particularly relevant to this study given the dominance of South African exports in bilateral trade flows within the region. Southern

78 The Zambian MFN and preferential tariff data series were constructed by Dale Mudenda.

79 The inclusion of the log distance squared term accounts for potential nonlinearities in the relationship between distance from the production location and the price in the consumption district.

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Africa represents one of the few settings in the world where well-grounded assumptions can be made on the direction of trade flows at the individual product-level. The assumption that products are produced in South Africa for consumption in the region allows for a focus on spatially relevant supplier to market pairs, while excluding potentially irrelevant market pairs between which trade in products does not occur. In the case of the latter, bilateral product price gaps are not directly informative of the magnitude of the cost of trade between market pairs (this is discussed in detail in Chapter 3). In contrast, price comparisons between product source and consumption destinations are “informative about international relative to local trade barriers” (Anderson & Van Wincoop, 2004: 740).

Given the dominant status of the Gauteng province as South Africa’s economic engine, it is assumed that all 14 products originate from the Gauteng region. In order to ensure that a price observation is included for each product in all years from 2002 to 2009, an average Gauteng price for each product and year is calculated using the prices for all districts in Gauteng for which a price observation is available in that particular year.⁸⁰ Bilateral road distances from Pretoria to all other districts included in the sample are used to account for the distance between the production location in Gauteng and the various consumption locations.⁸¹

In essence, the specification in equation (2) measures the extent to which the price of a particular product in consumption district c is related to the price of that product at its source (Gauteng), the transportation cost incurred in moving the product from Gauteng to the consumption district (which is proxied by the bilateral distance between district pairs), and the cost associated with crossing the border into Zambia in the case of the Gauteng-Zambia district pairs. The price of a non-traded service (men’s haircut) in the consumption districts is included in the specification to account for the influence of the cost of non-traded inputs on the final retail prices of products in those districts. This is necessary since final retail prices in a particular location are a function of the cost of both traded and non-traded inputs (Crucini et al., 2005a and 2005b).

80 For the period from 2002 to 2008, the Gauteng product price averages for each year are calculated using some combination of the prices in the Pretoria, Vanderbijlpark, Vereeniging and Witwatersrand districts (depending on which districts prices are observed for a particular product and year). In turn, the 2009 averages for each product are calculated using some combination of prices in the City of Johannesburg Metro, Ekurhuleni Metro, Pretoria, Vanderbijlpark, Vereeniging and Witwatersrand districts. The difference is due to changes in the sample of districts covered in the raw data between 2008 and 2009.

81 As before, distance is measured as the shortest road distance between district pairs. These distances are calculated from Google Maps using the longitude and latitude coordinates of the main city in each district (or the mid-point in districts not defined by a particular city).

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The key coefficients of interest in equation (2) are 𝛽₄ and 𝛽₅. The coefficient on the South Africa-Zambia border dummy measures the additional impact of crossing the border on the price of product i in consumption district c located in Zambia relative to the price in a consumption district in South Africa, after accounting for the influence of the distance from the production location (Gauteng). Without the inclusion of the interaction between the border dummy and the preferential tariff variable, 𝛽₄ would measure the unique effect of crossing the international border on the price of product i in the consumption district. Since the preferential tariffs only apply when crossing the Zambian border, the inclusion of the preferential tariff variable allows the effect of the border on the price in the consumption district to vary for different values of the preferential tariff rate. The coefficient on the interaction term, 𝛽₅, thus measures the marginal effect of the preferential tariff rate on the effect of crossing the national border on the retail price in the consumption district. It is anticipated that the effect of the border in raising the price of product i in the consumption location will be greater for higher values of the preferential tariff rate.

In analysing the effect of crossing the national border on the price of product i in consumption district c using the specification in equation (2), the bilateral district pairs involving Gauteng and another district within South Africa serve as a control. Importantly, however, as South Africa and Zambia are not contiguous countries, products exported from South Africa must first travel through either Botswana or Zimbabwe on their way to Zambia. Since South Africa and Botswana are both members of SACU, South African products are not subject to tariffs when crossing the border into Botswana. Thus, the border effect between South Africa and Botswana should be unrelated to any tariff effects on relative prices.

The addition of Gauteng-Botswana district pairs deals with potential omitted variable bias by accounting for the effect of crossing the Botswana-South Africa border on relative prices, and makes it possible to separate out these effects from the tariff effect on relative prices between South Africa and Zambia. It is anticipated that once accounting for the cost of trade, the price of product i in a consumption district in Botswana should be equal to the price of that product in Gauteng, 𝑝_{𝑖,𝑝,𝑡}; whereas the price of product i in a consumption district in Zambia should be equal to: 𝑝_{𝑖,𝑝,𝑡}(1 + 𝑝𝑡𝑎𝑟𝑖𝑓𝑓𝑍𝑎𝑚𝑆𝐴_𝑖,𝑡).

The augmented specification with the inclusion of the Gauteng-Botswana district pairs is thus:

𝑝𝑖,𝑐,𝑡= 𝛽0+ 𝛽1𝑝𝑖,𝑝,𝑡+ 𝛽2ln(𝑑𝑖𝑠𝑡𝑝𝑐) + 𝛽3ln(𝑑𝑖𝑠𝑡𝑝𝑐)²+ 𝛽4𝑏𝑜𝑟𝑑𝑒𝑟𝑆𝐴−𝐵𝑜𝑡𝑠𝑤𝑎𝑛𝑎+ 𝛽5𝑏𝑜𝑟𝑑𝑒𝑟𝑆𝐴−𝑍𝑎𝑚

+ 𝛽6𝑏𝑜𝑟𝑑𝑒𝑟𝑆𝐴−𝑍𝑎𝑚∗ 𝑙𝑛(1 + 𝑝𝑡𝑎𝑟𝑖𝑓𝑓𝑍𝑎𝑚𝑆𝐴𝑖,𝑡) + 𝛽7ln (𝑛𝑜𝑛𝑡𝑟𝑎𝑑𝑒𝑑𝑝𝑟𝑖𝑐𝑒𝑐,𝑡) + 𝛾𝑡+ 𝛾𝑖+ 𝜀𝑝𝑐,𝑡 (3)

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where 𝑏𝑜𝑟𝑑𝑒𝑟𝑆𝐴−𝐵𝑜𝑡𝑠𝑤𝑎𝑛𝑎 is a dummy variable equal to one if consumption district c is located in Botswana and zero otherwise; and the remaining variables are defined as for equation (2).

The baseline and augmented production-consumption pair specifications outlined above are used in the empirical analysis presented in the following section. The analysis examines the influence of tariffs on border effects in the SADC region by focusing on trade between South Africa and Zambia. This is achieved by empirical estimating the extent to which the presence of tariffs on South African products imported into Zambia contributes to cross-border dispersion in product prices between the two countries.