Specific Factors Model

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  Public Opinion on Economic Globalization

  Considering Immigration, International Trade, and Foreign Direct Investment

  • Roger White(Author)
  • 2017(Publication Date)
  • Palgrave Macmillan

    (Publisher)

  As we discuss the model and its predictions, we contextualize the information provided CHAPTER 3 Expected Winners and Losers: Economic Effects and Public Opinion Survey Responses © The Author(s) 2017 R. White, Public Opinion on Economic Globalization, DOI 10.1007/978-3-319-58103-3_3 52 R. WHITE in our earlier chapters. Moreover, by focusing our attention on the antici- pated welfare effects, our presentation of the model and theoretical framework better allows us to discern the expected preferences of survey respondents as they relate to economic phenomena. We employ the Specific Factors Model as a starting point and we then allow, when conducting our empirical analysis, for deviation from look- ing only at economic-based expectations such that we consider demo- graphic and/or individual-specific characteristics and, turning to our variable of primary interest, cross-societal cultural differences as determi- nants of public opinion. In a few words, this is the basis for our estima- tion strategy. We should note, however, that the version of the Specific Factors Model that is presented in this chapter is both basic and simple. This is useful in two ways. First, the simpler the model and its related presentation, the more accessible it will be for readers. Second, a simple version of the model is sufficient to allow us to discuss the findings pre- sented in Chap. 2 and to provide a basis for the empirical analysis that follows. Thus, in effect, we employ a theoretical framework that is only as complicated as is necessary and, therefore, which is as elegant as pos- sible, to motivate our efforts. 3.1 A VERY GENTLE INTRODUCTION TO THE Specific Factors Model We employ a standard 2 × 2 × 2 framework in which there are two economies (identified as home and as foreign), two sectors (which we refer to as X and Y) that, for simplicity, produce goods X and Y, respec- tively, and two factors of production (capital, which is denoted by K, and labor, which is denoted by L).

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  Lecture Notes on International Trade Theory and Policy

  • Richard Pomfret(Author)
  • 2008(Publication Date)
  • WSPC

    (Publisher)

  Despite its failure to explain interna-tional differences in factor rewards, especially the wide disparities in incomes between rich and poor countries, the factor price equali-sation theorem may be useful as a pointer to long-term tendencies. Anne Krueger (1968) argued that international differences in per capita incomes reflect differences in resource endowments, especially human capital, implying that investment in human capital in low-income countries would lead to convergence in per capita incomes. The rapidly rising incomes in the high-performing and open East Asian economies also suggest that trade is a path to convergence, although the evidence from cross-country growth studies is that con-vergence is conditional on many things, especially good institutions. The Specific Factors Model In the partial equilibrium model of the previous chapter producers of the import-competing good and consumers of the export good are the losers from trade. How can this emphasis on sectors be reconciled 48 Lecture Notes on International Trade Theory and Policy with the above emphasis on factors in analysing the distributional impact of trade? The answer depends upon the degree of factor mobility between sectors within a country. In the Specific Factors Model developed by Paul Samuelson (1971) and Ron Jones (1971) some factors are assumed to be sector-specific. Suppose that the production of food requires labour and land and the production of cloth requires labour and capital. Land and capital are specific factors and labour is mobile. The mobile factor will be allocated between sectors so that the value of its marginal product is the same in each sector, and equal to the wage rate. Figure 6.2 shows the labour demand curves in the cloth and food sec-tors (VMP c and VMP f ), with the origins chosen so that the length of the horizontal axis, O c O f , is equal to the total labour supply.

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  Routledge Revivals: International Trade (1986)

  Theoretical Issues

  • Bharat Hazari(Author)
  • 2018(Publication Date)
  • Taylor & Francis

    (Publisher)

  Before proceeding to present the Jones model it is important to spell out the rationale behind sector specificity of factors of production. There exist at least three different types of sector specificity. First, there is preferential specificity — a case in which the factor prefers to be employed in one sector rather than the other. For example, labour working on the night shift may demand a premium for night work. Preferential specificity may generate a model of wage differentials. Such a model was first presented by Lancaster (1958) and later explored among others by Manning and Sgro (1975). Second, factors may be specific in the aptitudinal sense — thus a factor of production may have comparative advantage in producing one commodity rather than the other. Note that when a factor of production has an infinite preference for working in a sector the system reduces to the pure Jones model. The third type of factor specificity is policy-imposed. For example, a metropolitan country may not necessarily allow foreign factors to be employed in all sectors of the economy and may impose restrictions on their mobility. A similar situation could arise when a Third-World government, for various non-economic objectives, might not allow foreign factors to be employed in all sectors of the economy. In fact, due to government regulations the foreign factors of production may be employed as specific factors of production.

  15.1 The Jones Model with Sector Specificity

  We now proceed to present the Jones model. This model may be viewed as an extension of the Ricardian system of comparative advantage where each sector has a fixed and non-transferable quantity of a specific factor, for example, capital K1 , and capital K2 .2 Both sectors use one mobile factor, labour. Let us suppose that commodity X1 is produced with a fixed quantity of capital K1 and commodity X2 with a fixed quantity of capital K2 and labour.

  The above system can be represented in terms of a box diagram which can also be used to generate the production possibility locus. In Figure 15.1 the horizontal distance represents the total endowment of the mobile factor labour. The vertical distance represents the magnitude of capital which is used by sector 1 only. Therefore, all solutions with full utilization of capital for sector 1 must be on the horizontal line . Sector 2 is represented from the origin O2 . This sector has a fixed supply of sector-specific capital. Therefore, given the assumption of full utilization of capital in sector 2 the solutions for this sector must also be on the line . Hence, the contract curve in the specific-factor case becomes instead of O1 EO2 in the non-specific-factor case. Two features should be noted. First, there is only one point which is common to both the production possibility curves, namely the non-specific and specific-factor cases. This is shown in Figure 15.2 by point P. Second, only the real wage will be equalized between the sectors (because labour is fully mobile). The return to the specific factor would generally be different across the sectors, as is shown by point E′ in Figure 15.1 . Only in the limiting case would the factor prices across sectors be equalized — as shown by point E. Since E′ is off the normal contract curve and is characterized by inequality in the marginal rates of substitution between sectors the production possibility curve of the sector-specific case must be dominated by the production possibility curve of the non-specific case, as is shown in Figure 15.2 . Note that except at point E

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  Introduction to Computable General Equilibrium Models

  • Mary E. Burfisher(Author)
  • 2021(Publication Date)
  • Cambridge University Press

    (Publisher)

  6 Factors of Production in a CGE Model In this chapter, we explore factor markets in a computable general equilibrium (CGE) model. Data in the Social Accounting Matrix (SAM) on factors of production describe factors’ sources of employment and income. Important factor market concepts in the CGE model are factor mobility assumptions, the effects of factor endowment and productivity growth, complementary and substitute factors, full-employment versus unemployment model closures, and the links between changes in factor supply and industry structure and between changes in industry structure and factor prices. Factors of production are the labor, capital, land, and other primary resources that producers combine with intermediate inputs to make goods and services. A nation’s factor endowment is its fundamental stock of wealth because factors represent its supply of productive resources. In Chapter 5, we considered production activities’ demand for factors and how these adjust with changes in relative factor prices or output levels. Many other dimen- sions of factor markets in a computable general equilibrium (CGE) model also deserve study. In the next sections, we describe factor markets in standard CGE models in detail, focusing on those aspects that are of greatest practical importance for CGE modelers. We begin by studying the factor market data in the SAM. Then we consider the behavior of factor markets in the CGE model. We explain factor mobility assumptions, which govern the readiness of factors to change their employment in response to changing wages and rents across industries. We explore the effects of changes in the supply, or endowment, of factors and contrast them with changes in the “effective” endowment when factor productivity changes. We study the implications of assuming produc- tion functions, or industry technologies, that treat factors as complements (low factor substitutability) versus substitutes (high factor substitutability).

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  Applied International Economics

  • W. Charles Sawyer, Richard L. Sprinkle(Authors)
  • 2020(Publication Date)
  • Routledge

    (Publisher)

  mobile factor because over time it can move between machine production and cloth production. Remember, when trade opens up between the U.S. and India, the machine industry expands and the cloth industry contracts in the U.S. Initially, if all factors of production are immobile, as the cloth industry contracts, both capital and labor in this industry suffer losses as employment contracts and factories are shut down. In the expanding machine industry, both labor and capital benefit as employment and profits increase. In fact, these initial industry-specific effects often dominate the political debate over trade policy within a country.

  Now, suppose that labor can move between industries and capital is immobile. Point E in Figure 4.1 illustrates the before-trade equilibrium for the U.S. In the figure, the total supply of

  FIGURE 4.1

  Specific-factors model

  With the specific-factors model, as the demand for labor in the machine industry increases the wage rate rises and workers move from the cloth industry to the machine industry.

  labor is shown along the horizontal axis. The amount of labor employed in the machine industry is measured from O rightward along the axis, and the amount of labor employed in the cloth industry is measured from O¢ leftward along the axis. In each industry, labor is combined with a fixed amount of specific capital to produce either cloth or machines. Under these conditions, labor is subject to diminishing returns in each industry. This means that the demand for labor in each industry is downward sloping and is equal to the value of the marginal product of labor.14 The machine industry’s demand for labor is represented by DM , and the cloth industry’s demand for labor is represented by DC . (The cloth industry’s demand for labor is measured leftward from O¢.) By assuming that labor is mobile between industries, both the machine industry and the cloth industry will pay the same wage rate, W0

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  Workbook in Introductory Economics

  • Colin Harbury(Author)
  • 2014(Publication Date)
  • Pergamon

    (Publisher)

  CHAPTER 4 Distribution: Factors of Production and their Prices The study of factors of production plays a double role in economics. It helps to answer two of the main questions referred to at the beginning of this book: (1) how production is best organized (because factor prices and productivities lie behind the cost curves of firms) and (2) for whom goods are produced (because the prices of factors of production lie behind the distribution of incomes). Market determination of the prices of factors of production, labour, capital and land, is analysed in a manner closely paralleling that used for the prices of goods and services — by studying the forces of supply and demand. DEMAND The demand for the services of a factor of production is the schedule of quantities which businesses want to buy at varying prices during a period of time. The demand is said to be DERIVED from the value of the goods which a factor produces. It is determined by a factor's productivity and the ease with which it may be substituted for other factors. The elasticity of demand for a factor depends on these influences, on the time allowed for a price change to take effect and on the relative importance of the factor in total costs. The technical efficiency, or productivity, with which factors of production can be combined to produce given outputs (the PRODUCTION FUNCTION) is a basic determinant of the costs of a firm. When the prices of the services of factors are known, a firm is able to select the least cost combination for each level of output. Productivity depends critically upon whether the short period or the long period is under consideration. The short period is defined as that during which at least one of the factors is fixed in supply. As units of a VARIABLE factor are used together with a fixed one, the MARGINAL PHYSICAL PRODUCT (M.P.P.) of the variable factor tends eventually to fall. This phenomenon is known as the LAW OF DIMINISHING RETURNS.

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  New Developments in Productivity Analysis

  • Charles R. Hulten, Edwin R. Dean, Michael Harper, Charles R. Hulten, Edwin R. Dean, Michael Harper(Authors)
  • 2007(Publication Date)
  • University of Chicago Press

    (Publisher)

  The index number approach also does not provide detailed insight into the dynamics of the production process and the determinants of factor demand and factor accumulation. The dynamic factor demand modeling approach reviewed in this paper provides a general framework to estimate the structure of the underlying technology and to relate the investment decisions and variation of technical change. Of course, in this approach there is, as in any other econometric investigation, the danger of misspeci-fication. However, the basic appeal of this modeling strategy is its flexibil-ity, that enables it to incorporate and analyze in a consistent framework both theoretical considerations and institutional factors that influence technical change, and to test various hypothesis concerning the specifica-tion of the technology and the optimizing behavior of the firm. The dynamic factor demand modeling framework described in this pa-per enables us to examine a number of issues of both basic research and policy interest. Using the model it is possible to identify the possible biases in the conventional measure of total factor productivity growth. These biases can result from scale e ff ects, the di ff erence between marginal prod-ucts and long-run factor rental prices in temporary equilibrium due to adjustment costs, the direct e ff ect of adjustment costs as they influence Dynamic Factor Demand Models and Productivity Analysis 155 output growth, and the selection of the depreciation rate by the firm. The model presented in this paper can be used to estimate the structure of the underlying technology and to specify the magnitudes of these biases if they are present. If the biases are not isolated, relying on the conventional TFP measure will, for example, overestimate technical change in the pres-ence of increasing returns to scale and positive output growth.

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