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Health care costs in the United States are much higher than in other countries. These cost differences can be explained in part by a lack of competition in the United States. Some markets, such as pharmaceuticals and medical equipment, have elements of monopoly. Other markets, such as health insurance, have elements of monopsony. Many other markets may be subject to collusion on prices, such as generic drugs, or wages, such as the nurse labor market. Lawful monopoly and monopsony are beyond the reach of antitrust laws, but collusion is not. When appropriate, vigorous antitrust enforcement challenging anticompetitive conduct can aid in reducing health care costs. This book addresses monopoly, monopsony, cartels of sellers and buyers, horizontal and vertical merger policy, and antitrust enforcement through private suits as well as the efforts of the antitrust Agencies. The authors demonstrate how enforcing antitrust laws can ultimately promote competition and reduce health care costs.
Chapter 10 surveys a range of partial survey and non-survey estimation approaches for creating input–output tables at the regional level. Variants of the commonly used class of estimating procedures using location quotients are reviewed; these presume a regional estimate of input–output data can be derived using some information about a target region. Cross-hauling is discussed and approaches to address it are presented. The RAS technique developed in Chapter 9 is applied using a base national table or a table for another region and some available data for the target region. Techniques for partial survey estimation of commodity flows between regions are also presented along with discussions of several real-world multinational applications, including the China–Japan Transnational Interregional Model and Leontief’s World Model.
Chapter 11 expands the input–output framework to a broader class of economic analysis tools known as social accounting matrices (SAM) and other so-called extended input–output models to capture activities of income distribution in the economy in a more comprehensive and integrated way, including especially employment and social welfare features of an economy. The basic concepts of SAMs are explored and derived from the SNA introduced in Chapters 4 and 5, and the relationships between SAMs and input–output accounts are presented. The concept of SAM multipliers as well as the decomposition of SAM multipliers into components with specific economic interpretations are introduced and illustrated. Finally, techniques for balancing SAM accounts for internal accounting consistency are discussed and several illustrative applications of the use of SAMs are presented.
The introductory chapter recaps the genesis of the field of input–output or interindustry analysis as a widely utilized framework to analyze the interdependence of industries in an economy. The introduction chronicles how the input–output framework, conceived originally by Wassily Leontief in the 1930s, has matured over the last seven decades to become a key component of many types of economic analysis and one of the most widely applied methods in economics. This book presents the framework set forth by Leontief and explores the many extensions that have been developed, and the introduction concludes by summarizing the key features of the succeeding chapters, appendices, and related online resources chronicling those developments.
The Preface recaps the history of the development of the 1985, 2009, and current editions of the text and how the content has evolved with the discipline of input–output analysis. It also includes a summary of the principal updated and added material in this new edition.
Chapter 15 briefly describes some additional extensions to input–output analysis for which space does not permit a detailed treatment in this text, including measuring total factor productivity, modeling economic impacts of disasters, the inoperatbility input–output model, accounting for alternative technologies, and linkages to econometric or computable general equilibrium models.
Chapter 9 introduces approaches designed to deal with the major challenge in input–output analysis that the kinds of information-gathering surveys needed to collect input–output data for an economy can be expensive and very time consuming, resulting in tables of input–output coefficients that are outdated before they are produced. These techniques, known as partial survey and nonsurvey approaches to input–output table construction, are central to modern applications of input–output analysis. The chapter begins by reviewing the basic factors contributing to the stability of input–output data over time, such as changing technology, prices, and the scale and scope of business enterprises. Several techniques for updating input–output data are developed and the economic implications of each described. The bulk of the chapter is concerned with the widely utilized biproportional scaling (or RAS) technique and some related “hybrid model” variants.
Chapter 6 examines a number of key summary analytical measures known as multipliers that can be derived from input–output models to estimate the effects of exogenous changes on (1) new outputs of economic sectors, (2) income earned by households resulting from new outputs, and (3) employment generated from new outputs, (4) value-added generated by production, or (5) energy and environmental effects. The general structure of multiplier analysis and special considerations associated with regional, IRIO, and MRIO models are developed. Extensions to capture the effects of income generation for various household groups are explored, as well as additional multiplier variants. Chapter appendices expand on mathematical formulations of household and income multipliers.
Chapter 5 explores variations to the commodity-by-industry input–output framework introduced in Chapter 4, expanding the basic input–output framework to include distinguishing between commodities and industries, i.e., the supply of specific commodities in the economy and the use of those commodities by collections of businesses defined as industries. The chapter introduces the fundamental commodity-by-industry accounting relationships and how they relate to the basic input–output framework. Alternative assumptions are defined for handling the common accounting issue of secondary production, and economic interpretations of those alternative assumptions are presented. The formulations of commodity-driven and industry-driven models are also presented along with illustrations of variants on combining alternative assumptions for secondary production. Finally, the chapter illustrates the problem encountered with commodity-by-industry models, such as non-square commodity–industry systems, mixed technology options, or the interpretation of negative elements.
Chapter 2 introduces Leontief’s conceptual input–output framework and explains how to develop the fundamental mathematical relationships from the interindustry transactions table. The key assumptions associated with the basic Leontief model and implications of those assumptions are recounted and the economic interpretation of the basic framework is explored. The basic framework is illustrated with a highly aggregated model of the US economy. In addition, the “price model” formulation of the input–output framework is introduced to explore the role of prices in input–output models. Appendices to this chapter include a fundamental set of mathematical conditions for input–output models, known as the Hawkins–Simon conditions.
Chapter 13 reviews the extensions of the input–output framework to incorporate activities of environmental pollution and elimination associated with economic activities as well as the linkages of input–output to models of ecosystems. The chapter begins with the augmented Leontief model for incorporating pollution generation and elimination, from which many subsequent approaches have been developed. The chapter then describes the now widespread application of input–output analysis to environmental lifecycle assessment and establishing a “pollution footprint” for industrial activity. Environmental input–output is also now widely used to evaluate global environmental issues. The special case of analyzing the relationship between global climate change and industrial activity with a carbon footprint is then explored along with using input–output to attribute pollution generation to the demands driving consumption compared with the more traditional attribution of pollution generation to the sectors of industrial production necessary to meet that demand.
Chapter 8 introduces and illustrates the basic concepts of structural decomposition analysis (SDA), in both additive and multiplicative forms, within an input–output framework. The concept of decomposition of the various types of multipliers is introduced and explored further in Chapter 11, as applied to Social Accounting Matrices (SAMs). The application of SDA to MRIO is developed to introduce a spatial context. Numerous applications are cited and summaries of their results are presented. Appendices to this chapter develop extended presentations of additional decomposition results as well as an overview of early applied studies and some further mathematical results.
Chapter 7 presents the so-called supply-side input–output model. It is discussed both as a quantity model (the early interpretation) and as a price model (the more modern interpretation). Relationships to the standard Leontief quantity and price models are also explored. In addition, the fast-growing literature on quantification of economic linkages and analysis of the overall structure of economies using input–output data is examined. Finally, approaches for identifying key or important coefficients in input–output models and alternative measures of coefficient importance are presented.
Chapter 14 describes so called mixed input–output models that are driven by a mix of output and final demand specifications rather than driven either solely by specification by final demand or total output. This chapter also introduces dynamic input–output models that more explicitly capture the role of capital investment and utilization in the production process.
In this text we have developed the basic framework of input–output analysis and many of the extensions and applications that followed Professor Leontief’s seminal work defining the field nearly seven decades ago (chronicled in Appendix C). To this day, input–output and its extensions endure by themselves as tools for many kinds of economic analysis. The basic framework often comprises a fundamental component of many other types of economic analysis as well, such as econometric general equilibrium and planning models, and extensions also include applications to broader social accounting problems, such as social accounting matrices, ecological analysis, tracing material or energy use and flow throughout an economy measured in physical terms, or defining material or environmental footprints for firms, regions, or nations. We have captured many, and perhaps most, but not all these extensions and applications to varying degrees of detail in this text.