Multi-sector specific factors model with two mobile factors

Trade and factor returns: Empirical evidence from U.S. economy

The role of labor endowments on industry output in the short run: Evidence from U.S industries

In this paper we examine the relationship between labor supply and industry-level output in the context of the specific factors model. Jones (Trade, balance of payment and growth: essays in honor of Charles P. Kindleberger, Amsterdam, pp 3–21, 1971) shows that a rise in the amount of labor in the economy will increase the output in all industries. We empirically show which industry output is predicted to expand more when the size of labor force grows. Unlike the commonly used Rybczynski Theorem (Economica 22:336–341, 1955) of the Heckscher-Ohlin model, the specific factors model shows that a comparison both of labor intensities and labor demand elasticities plays an important role in determining which output expands relatively more when the size of labor force grows. For this purpose, we illustrate the importance of the parameters of the model in determining how changes in the labor supply affect the output change, with special reference to elasticities of substitution in production. We estimate the elasticity of substitution by using CES production function and show how these estimates describe the general equilibrium of production with one mobile factor (labor) and 25 industries of the US economy using data for 1979–2001. We show that the increase in the supply of labor raise output in all industries, but the magnitudes of the increases in some industries are more than others depending on the value of the elasticity of substitution along with factor intensities between industries. The largest output effect occurs for educational, health care and social service, where a 1 % supply of labor increase would raise output 10.5 %. However, the growth in the labor supply has a small impact on output growth in the range of 0.1–0.6 % in agriculture, petroleum, coal product and finance and insurance industries.

Bullwhip effect under substitute products

In a recent article, Amano (1977) used a two-commodity, three-factor model, developed by Jones (1971) and extended by Mayer (1974) and Mussa (1974), to analyse the role of specific factors in international trade and investment. His analysis concentrated on two aspects: first, on examining the importance of specific and mobile factors in determining comparative advantage in this structure; second, on commenting on certain features of Caves' (1971) consideration of the determinants and consequences of international investment in this framework, in which foreign investment is viewed as inter-country flows of industry-specific capital. The purpose of this paper is to extend Amano's analysis into a new structure, which combines elements of the standard Heckscher-Ohlin-Samuelson (H-O-S) and specific factor (SF) models, and is better equipped to handle international mobility of specific factors. The difficulty with the SF, as with H-O-S, model, when all capital is internationally mobile, is that the location of world production is then indeterminate. Within a certain range, therefore, the movement of capital from one country to the other merely alters the location of production, without altering its total. As Amano notes, this property implies that any tariff is prohibitive, short of specialization, since capital flows, responding to the return differential created by the tariff, simply relocate production until trade, at least in the sense of a two-way commodity flow, is eliminated. A one-way commodity flow may continue if foreign earnings are repatriated. But unless factor movements are restricted or taxed, the tariff alone loses all flexibility as a method of adjusting domestic production. Since this is both a strong and largely undesirable property, the development of a new structure, which retains most of the traditional features of trade models yet permits capital mobility without such extreme consequences, seems worthwhile. Section I gives a brief diagrammatic exposition of Amano's results for the SF model, and the consequences of full capital mobility. Section II then introduces our hybrid structure, and relates the determinants of comparative advantage and the consequences of capital mobility to those discussed by Amano. The fact that all the main ingredients are familiar from the H-O-S and SF models considerably facilitates our discussion.

This paper analyzes the effects of changes in relative commodity prices on the distribution of income among factors of production in the context of two models of a simple, two-good economy. In the first model capital is treated as a specific factor in each industry, with labor mobile between industries. The assumption of specificity determines the direction of factor income changes, with magnitudes depending on substitutability between factors and on intensities of factor use within the two industries. In the second model, capital is viewed as a quasi-fixed factor. For the short run, this model is identical to the model first considered. For the long run, this model is identical to the Stolper-Samuelson model in which the direction and magnitude of factor income changes depend solely on relative factor intensities. The difference between the short-run and long-run determinants of changes in factor incomes gives rise to a conflict between factor owners' short-run and long-run interests.

In 2004 the United Nations University World Institute for Development Economics Research (UNU-WIDER) embarked on a large-scale research project on the ‘Impact of Globalization on the World’s Poor’ co-directed by Machiko Nissanke and Erik Thorbecke. The first conference was essentially conceptual in nature, meant to understand better the various mechanisms and channels through which globalization affects the poor either directly or indirectly. The other three conferences focused on each of the major regions of the developing world: Asia, Africa and Latin America. Theobjectivesofthisintroductionarethreefold:first,toreviewbrieflyhow the forces of globalization influence poverty in general; second, to describe and discuss the main transmission channels and mechanisms; and third to analyze the impact of globalization on Africa and present an overview of the six Africa case studies included in this issue. 1. The Impact of Globalization on the World’s Poor Globalization provides a strong potential for a major reduction in poverty in the developing world because it creates an environment conducive to fastereconomicgrowthandtransmissionofknowledge. 1 However,structural factors and policies within the world economy and national economies have impeded the full transmission of the benefits of the various channels of globalization for poverty reduction. In particular sub-Saharan Africa (SSA) hasbeenrelativelylessaffectedbytheforcesofglobalizationthanotherparts of the world. World income distribution continues to be very unequal and many poor countries particularly in Africa are stagnating. Moreover, there is much empirical evidence that openness contributes to more within-country

The 45 region by 50 commodity by 5 primary factor version of the GTAP database provides us with the splits of total labor payments into two categories, viz. skilled and unskilled labor in each sector. The decomposition of total labor payments in all sectors and all regions according to differentials in the skill content of the labor force presupposes substitution possibilities between these two categories of labor. Our interest is to explore the elasticity of substitution implicit in this disaggregation of occupation types. Given the skilled labor payment shares (as calculated from the GTAP database), we offer an ex post rationalization of them within a production-theoretic framework, thereby deriving estimates of the elasticity of substitution between skilled and unskilled labor. The adoption of a suitable nesting of skilled and unskilled labor in GTAP's production function enables us to find a 'reasonable' value for the substitution elasticity that is implicit between the two categories of labor in the GTAP database. This relies on the inter-regional covariation in the GTAP shares and in measures of educational attainment. JEL classification: J24, J31, O15 Keywords: Elasticity of substitution; Educational attainment; Skilled and Unskilled Labor

Accounting for Skill Premium Patterns During the EU Accession: Productivity or Trade?

This article looks at the relative importance of competing stories, particularly trade liberalization and skill-biased technical change, to explain changes in the skill premium and the real wages of unskilled and skilled workers in Mexican manufacturing using plant-level data. The channel through which technical change is observed is changes in the domestic price of machinery and equipment due to the availability of new and cheaper machines. The analysis also looks at trade-induced skill-biased technical change by taking into account changes in the price of machinery and equipment caused by changes in the tariff rate specific to machinery and equipment. Instrumental variables, including the price of machinery and equipment in the United States, are used to determine causality between the above effects and wages. Thus, the article provides evidence for some recent findings in the literature that link trade liberalization, skill-biased technical change occurring through technology embodied in machines and increases in the skill premium.

Abstract‘Bubble’ diagrams are quite useful in revealing some of the properties found in the competitive models of international trade. These diagrams use circles (bubbles) to indicate commodity outputs and connecting lines to indicate factor inputs. Models such as the 2 × 2 and n × n Heckscher–Ohlin models as well as the 3 × 2 (and extensions) specific factors model are discussed. For example, a model with some factor mobility between countries (say capital into a foreign enclave) is discussed for both model types. As well, close analogies are made to issues in labour economics in which both skilled and unskilled labour are used as inputs.

Pricing and inventory replenishment are important operations decisions for firms such as retailers. To make these decisions effectively, a firm needs to know the demand distribution and its dependency on selling price, which is usually estimated using sales data at various testing price levels. Although more testing prices can lead to a better estimation of the demand–price relationship, frequent price changes are costly and come with adverse effect such as customers’ negative perception. In this article, data-driven algorithms are developed that learn the demand structure with constraints on the number of price changes. These algorithms are shown to converge to the optimal clairvoyant solution, and the convergence rates are the best possible in terms of profit loss.

Consider a small open Harris and Todaro's model. This paper analyzes the impact of the policy of environmental protection on skilled–unskilled wage inequality. We find that, in the economy with urban unemployment, if the elasticity of substitution between unskilled labor and pollution in the urban low‐skill sector is small (large) enough then a rise in the pollution tax will expand (narrow down) skilled–unskilled wage inequality. In addition, we prove that, in the economy with full employment, a rise in the pollution tax will raise the skilled–unskilled wage inequality, if the elasticity of substitution between unskilled labor and pollution is larger than that between capital and pollution in the urban low‐skill sector.

A continuous approximation method for dynamic pricing problem under costly price modifications

We study a multi-period stochastic inventory system with backlogs. Demand in each period is random and price sensitive, but the firm has little or no prior knowledge about the demand distribution and how each customer responds to the selling price, so the firm has to learn the demand process when making periodic pricing and inventory replenishment decisions to maximize its expected total profit. We consider the scenario where the firm is faced with the business constraint that prevents it from conducting extensive price exploration, and develop parametric data-driven algorithms for pricing and inventory decisions. We measure the performances of the algorithms by regret, which is the profit loss compared with a clairvoyant who has complete information about the demand distribution. We analyze the cases where the number of price changes is restricted to a given number or a small number relative to the planning horizon, and show that the regrets for the corresponding learning algorithms converge at the best possible rates in the sense that they reach the theoretical lower bounds. Numerical results indicate that these algorithms empirically perform very well. Supplementary materials are available for this article. Go to the publisher’s online edition of IISE Transaction, for datasets, additional tables, detailed proofs, etc.