Economics versus politics in trade policy

Abstract

Do economies of scale contribute to our understanding of trade policy or is ideology and inequality sufficient? We develop a unified theoretical framework that encompasses both strategic economic and political variables deemed to be important in explaining trade policy. We predict that an increase in the scale effect leads to restrictive trade policies in labor-abundant countries and liberal trade policies in capital-abundant countries. Using cross-country data on economies of scale, ideology, inequality and various measures of trade barriers we confirm our predictions and establish that a unified framework, which incorporates economies of scale in production, performs better in explaining trade policy than existing political economy models.

Appendices

Appendix 1: The model

The model is distinguished by non-tradability in intermediate inputs which renders the external economy of scale national in scope.²³ Production of each variety of intermediate inputs is done with identical production functions. The factor bundle required to produce x _i of a typical intermediate input is given by,

$$ f_{i} = b + ax_{i} . $$

(15)

The constant fixed and marginal costs b and a are positive and are identical across intermediates. Internal economies of scale in the production of intermediates rules out economically inconsistent outcomes by limiting the number of varieties produced. In equilibrium, each monopolistically competitive firm produces a unique variety of a differentiated intermediate input. The number of varieties produced equals the number of firms in the country. The intermediate inputs are combined to produce manufactures via the production function

$$ M = \left( {\sum\limits_{i = 1}^{n} {x_{i}^{B} } } \right)^{{{1 \mathord{\left/ {\vphantom {1 B}} \right. \kern-\nulldelimiterspace} B}}} , $$

(16)

where $\, 0 < {\text{B}} < 1$ is a substitution parameter that determines the value of the constant elasticity of substitution (which is given by ${1 \mathord{\left/ {\vphantom {1 {1 - \beta }}} \right. \kern-\nulldelimiterspace} {1 - \beta }}$), and n is the number of intermediate varieties produced, which itself is endogenously determined. In the symmetric equilibrium considered here, intermediate inputs are produced in equal quantities and the total quantity of intermediates produced is denoted by nx. Therefore, Eq. 16 reduces to

$$ M = n^{\alpha } x, $$

(17)

where $\alpha = {1 \mathord{\left/ {\vphantom {1 B}} \right. \kern-\nulldelimiterspace} B}$ indicates the degree of increasing returns to variety. Equation 17 displays constant returns to scale for a given value of n. The larger the variety of intermediate inputs, the greater the reward from external economies of scale and the lower the production cost. Average costs are decreasing in the number of available varieties of intermediate inputs.

The demand function facing a representative intermediate producer is derived by the minimization problem of the manufacturing firm [$Min\sum {P_{i} } x_{i} , \,$subject to (16)], where $P_{i}$ is the price of an intermediate input. For a pair of intermediate inputs, x ₁ and x ₂, the derived demand is $x_{1} = x_{2} \left( {{{P_{{x_{2} }} } \mathord{\left/ {\vphantom {{P_{{x_{2} }} } {P_{{x_{1} }} }}} \right. \kern-\nulldelimiterspace} {P_{{x_{1} }} }}} \right)^{{{1 \mathord{\left/ {\vphantom {1 {1 - B}}} \right. \kern-\nulldelimiterspace} {1 - B}}}}$, which has a constant price elasticity of

$$ \sigma_{x} = {\frac{\alpha }{\alpha - 1}}. $$

(18)

This is also the elasticity of substitution between a pair of intermediate inputs in the assembly of finished manufacture. Higher values of α indicate that components can be less easily substituted. From (15), the total cost of a representative intermediate input producer is $P_{f} (b + ax)$, where P _f is the price of a factor bundle. Subscript i is dropped due to the symmetry across the intermediate inputs. An intermediate input producer equates marginal revenue $\left( {{{P_{x} } \mathord{\left/ {\vphantom {{P_{x} } \alpha }} \right. \kern-\nulldelimiterspace} \alpha }} \right)$ to marginal cost $\left( {P_{f} a} \right)$ and obtains the price of an intermediate input

$$ P_{x} = \alpha P_{f} a \, , $$

(19)

where α represents a constant mark-up over marginal cost. In the monopolistically competitive market for the intermediate inputs, profits are driven to zero in the long run by free entry. This yields the quantity of a distinct intermediate produced

$$ x = {\frac{b}{{\left( {\alpha - 1} \right)a}}}. $$

(20)

Thus, x is uniquely determined by the parameters. Summing (14) over i, we obtain

$$ f = n\left( {a + bx} \right), $$

(21)

where f is total quantity of the factor bundle used in the production of intermediates. Using (19) and (20), we determine the number of varieties produced

$$ n = {\frac{{\left( {\alpha - 1} \right)f}}{b\alpha }}. $$

(22)

For high values of α, the higher is the value of variety for the manufacturing firm, the higher the number of varieties produced and the lower the quantity of each intermediate variety produced.

Denoting by P _M the competitive supply price of manufactures, an individual manufactures’ zero profit condition leads to

$$ P_{M} M = P_{x} nx. $$

(23)

The manufacturing industry is competitive with constant returns to scale at the plant level. An increase in the number of intermediate varieties leads to higher than proportional increase in the production of manufactures. Since the manufacturing firm desires diversity in intermediate inputs, there will be scale economies external to the firm but internal, at the national level, to the industry.

Marshallian production stability requires that the supply price of manufactures be positively sloped. As a result, we assume normal price output response where an increase in price leads to increased output. This condition is satisfied under mild economies of scale, where the factor intensity effect dominates the scale effect.²⁴

Appendix 2

See Table 5.

Table 5 Summary statistics

Appendix 3: Data sources

(Tariff):

: Barro and Lee (1994)

(TR):

: Barro and Lee (1994)

(Scale):

: Baier et al. (2006)

(IN):

: Deininger and Squire (1996). For cross-country comparability of inequality measure, add 6.6 to the expenditure-based Gini coefficients. This is the average difference between expenditure-based and income-based coefficients

(ID):

: Beck et al. (2000)

(K/L):

: Easterly and Levine (2002) (in natural logs)

(D-East-Asia):

: Barro and Lee (1994)

(D-Oil):

: Easterly and Kraay (2000)

(D-SSA):

: Easterly and Levine (1997)

(DEM):

: Democracy Country Ratings (Gastil index)

(LANDGINI):

: Deininger and Squire (1998)

(FD):

: Li et al. (1998). Financial depth is M2/GDP

(SCH):

: Barro and Lee (1994). Average schooling years in the total population over age 25

(CIVLIB):

: Democracy Country Ratings (Gastil index)

(SAVRATE):

: World Development Indicator (1997)

(POPGRATE):

: World Development Indicator (1997)