Knowledge that Transforms

FOR at least the last two decades the South and Southwest have been the fastest growing regions in the United States. During this period we have witnessed considerable shifts in the location of economic activity and, overall, the movement has been decidedly toward the South. Since the early sixties, when this southern migration began to accelerate, an increasing amount of public attention has been directed to this topic; so much so that it is now popularly referred to as the Sunbelt phenomenon. Numerous explanations have been advanced to account for this rapid growth in the South, but three explanations have persistently evoked an impressive level of debate. First, many have argued that a significant portion of this regional redistribution can be attributed to differentials in state and local taxing policies; in particular the state corporate income tax. These rates vary considerably across states, but even more important is the observation that there have been significant changes in the structure of corporate taxes over the last few decades. Beginning in the early 1950s the relative tax rate' for several southern states, particularly those in the East South Central and West South Central divisions, began to decline sharply. On the other hand, relative tax rates for three divisions, New England, the East North Central and the MidAtlantic, rose in the early sixties. By 1970 the relative tax rate ranged from 0.60 in the West South Central (down from 1.20 in 1950) to 1.37 in the Mid-Atlantic (up from 1.15 in 1950). Notwithstanding these stylized facts, the consensus from previous empirical work on industry location suggests that state taxes have not influenced the direction or magnitude of industry migration. However, there are reasons to believe that acceptance of this conclusion may be premature. For example, in the early body of work, results were based on simple correlations of tax levels and changes in either value added or employment.2 More recent attempts to empirically model corporate tax effects have arrived at somewhat ambiguous results. Carlton (1977), examining three 4-digit industries, found that corporate tax differentials failed to explain any of the variation in new births of firms across SMSAs. Hodge (1979), while confirming Carlton's results for the same industries, discovered that taxes have significantly affected regional investment patterns in another industry not covered in Carlton's study.3 Why taxes mattered in one industry and not in the other three remained a matter of ad hoc speculation. A second explanation alleges that states in the South have begun to exhibit a more favorable business climate. Although it is difficult to measure directly a state's business climate, one important manifestation of that climate is its position with respect to the division of power between union and management in the collective bargaining process. Legal obstacles to union organization and bargaining power will be viewed by firms as a positive signal of a pro-business environment. The creation of legislative obstaReceived for publication October 29, 1981. Revision accepted for publication April 16, 1982. Miami University. The author is especially indebted to Michael Ward at the Rand Corporation for numerouls helpful discussions throughout the preparation of this study. Also, the author benefited from the advice and comments of John Antel, Robert Cotterman. Lee Lillard, John Lunn, William J. Moore, James Smith, Finis Welch and two referees of this REVIEW. Financial suppoI-t was provided by the Foundation for Research in Economics and Education at UCLA and the University of British Columbia Humanities and Social Sciences Committee. I The relative tax is defined as a state's tax rate divided by the average for all states. As in most economic discussions, it is relative price that matters. 2 For a review of earlier work see Due (1961). Some of the studies reviewed include Bloom (1955), Campbell (1958), Floyd (1952), and Larson (1957). See also Garwood (1952). 3 Most of the other empirical work focused exclusively on intt--urban location decisions and hence had no reason to examine state corporate taxes. However, they found local tax differentials (inter-zonal) were unimportant in determining intra-urban movement. For example, see Moses and Williamson (1967) and Schmenner (1978).

During the last two decades the issue of equality according to sex and race has become one of increasing importance to economists. An extant literature on the economics of discrimination began with the pioneering work of Becker (1957). This paper is an attempt to shed further light on the extent of employer discrimination by sex and race by comparing the earnings of self-employed workers to their wage and salary counterparts. In short, if employer discrimination is a principal source of discrimination against blacks and women, then we would expect the black/white and female/male earnings ratios to be higher for the self-employed compared to their wage and salary counterparts. No discrimination of this type is applicable to self-employed workers. In addition, blacks and women should be relatively overrepresented among the self-employed compared to wage and salary workers in the economy. Section II of this paper further elaborates on this indirect method to estimate the extent of employer discrimination in the labor market for blacks and women. In section III, the results of this method are presented using the 1978 Current Population Survey as the data source. Results indicate the black/white and female/ male earnings ratios are no larger for the self-employed compared to their wage and salary counterparts, even after making various attempts to adjust for differences in other variables that affect earnings, and to limit the influence of consumer discrimination on the results.

THE study of merger activity has been of long-standing interest to economists as well as the financial community. References to merger activity in American industry generally acknowledge three major merger movements. The first one occurred during the turn of the century, the second one during the 1920s. Stigler (1950) describes the second merger wave as being for oligopoly in contrast with the earlier for monopoly movement. Increased market power through consolidation and corporate concentration and operating economies of scale were identified as motives for mergers during these two waves. Horizontal mergers (i.e., mergers between direct competitors) were relatively more important during the first merger wave with vertical mergers (i.e., mergers between firms with prior buyer-seller relationships) being significant in the second wave.' Currently the United States is in the midst of its third major merger wave which began after the end of World War II. This has become known as the conglomerate merger wave because of the emphasis on mergers between unrelated firms or firms seeking product extension objectives (i.e., mergers between firms functionally related in terms of distribution and/or production facilities but whose products are not directly competing).2 The direction of the current merger wave can be partially explained by the fact that the Celler-Kefauver amendment to the Clayton Act in 1950 discourages horizontal and vertical mergers. While many authors have engaged in the study of mergers in the United States, the empirical examination of changes in aggregate merger activity has been limited both as to type and time period covered. Nelson (1959) first examined changes in quarterly merger activity during the 1895-1920 period and found a high positive correlation between changes in merger activity and changes in stock prices, and a positive but lower correlation between mergers and industrial activity. Further study by Nelson, however, showed that for the 1919-1954 period the relationship between mergers and stock prices was considerably weaker. In a follow up study, which extended aggregate merger data through 1962, Nelson (1966) concluded that merger activity exhibited a positive and highly consistent response to changes in business activity (as measured by the reference or business cycle). In addition to the efforts by Nelson, Weston (1961) examined annual changes in merger activity during the interwar period (between World War I and World War II). Using a multiple regression model, Weston found merger activity to be significantly related to stock prices but not significantly related to industrial production activity. Previous studies provide only limited insights into the structural (especially lead-lag) relationships between aggregate merger activity and macroeconomic/market factors. The literature is particularly void of empirical studies which investigate such relationships during the current merger period.3 It is this subject which we address in this paper. We employ a data-based multiple time series approach to develop an explanatory model for describing changes in the incidence of Received for publication July 14, 1981. Revision accepted for publication December 17, 1982. * University of Colorado, University of Iowa, and University of Denver, respectively. Computer facility support from the University of Iowa along with multiple time series programs provided by the University of Wisconsin-Madison are gratefully acknowledged. We also wish to thank the referees for their helpful comments. ' These two merger waves or movements were extensively studied, either separately or together, by Eis (1969), Markham (1955), Nelson (1959), Stigler (1950), Thorp (1941), and Weston (1961), as well as others. 2 The current merger movement, either separately or in conjunction with the earlier movements or waves, was analyzed by Lintner (1971), Lynch (1971), Markham (1973), Nelson'(1966), Reid (1968), and Steiner (1975). 3 International investigation of aggregate merger activity during the 1960s and 1970s is reported in Mueller (1980). Visual examination of the movement of mergers, GNP, and stock prices in Belgium suggested generally positive relationships. Aggregate merger activity was compared individually against economic activity (GDP), gross fixed investment, and share prices in West Germany. During the 1960s mergers tended to move in step with changes in economic activity and investment while lagging share prices. However, in the 1970s merger activity tended to lead the other aggregate measures. The best overall relationship was between merger activity and share prices.

Laura Blanciforti, Richard Green, An Almost Ideal Demand System Incorporating Habits: An Analysis of Expenditures on Food and Aggregate Commodity Groups, The Review of Economics and Statistics, Vol. 65, No. 3 (Aug., 1983), pp. 511-515

THIS paper models and estimates import demand and demand for export functions for 19 industrial countries. Although primary emphasis is placed on the period of generalized floating exchange rates, 1972 through 1980, estimates are also provided for the fixed exchange rate years (1957-1970), thus making possible a comparison between the two eras. Aside from the conventional income and price variables, the paper assesses the effect of variations in the exchange rate and in the expected exchange rate, on real trade flows. Additionally, it estimates an unrestricted lag structure of the effect of price and exchange rate variations on imports.

sector) disaggregation, the change in the level effect accounts for only 0.35 (0.41) percentage point of the 2.24 percentage point deceleration in labor-productivity growth between the 1948-65 and 1973-78 periods. The aggregate rate and level effects are not very sensitive to the degree of disaggregation (12versus 60-sector). Although some large level effects are evident within and across major industrial divisions, they often cancel out in the aggregate. However, the level effect from the shift out of farming is quantitatively large and is close to the aggregate level effect using either 12-sector or 60-sector disaggregation. Although one can approximate the aggregate level effect by looking only at that for agriculture, one should note that other fairly large level effects exist both within and across major industrial divisions other than agriculture.

T HE dietary choice of households near subsistence levels of nutrient intake is one of obvious policy importance. In many countries, such as Bangladesh, national goals are set in terms of nutritional intake and there is heavy intervention in the markets for foods. However, little is known about the manner in which food preferences vary with food expenditure and nutrient intake. The design of efficient programs to aid nutritionally deficient households in attaining minimal levels of nutrient intake requires information on all ownand cross-price elasticities for both target and non-target groups. The net effect of a food price subsidy on the consumption of food nutrients cannot be predicted without knowledge of the complete elasticity matrix. Results presented below demonstrate that substitution effects can be so strong that the subsidization of certain foods quite often reduces nutrient consumption. In this study, demand equations for nine foods which allow for extremely flexible consumer price response are estimated from the individual budgets of 5,750 rural Bangladeshi households. Estimation at the household level is preferred because it more readily permits the incorporation of household composition variables into the demand analysis, such as household size, occupation and employment status, that are typically lost in aggregation. There is also a greater range and variation in expenditure levels than found in grouped data. This is of particular importance in the study of nutritional well-being as it is the poorest households which are of special interest. Moreover, the household sample provides sufficient degrees of freedom to estimate a simple varying parameter model which requires the estimation of 270 parameters. Previous econometric analysis of income-class specific dietary choice has been limited and not altogether satisfactory. Pinstrup-Anderson, de Londono and Hoover (1976) estimated complete sets of price elasticities for different income strata using Frisch's scheme in order to study the impact of changes in relative prices on nutrient consumption. Their results are suspect because of the assumption of want independence necessary for this methodology to be valid. Alderman and Timmer (1980), who were also concerned with studying the relationship between food price policy and nutrient intake by income classes, econometrically estimated separate price coefficients for each income group by including slope dummy variables in their demand equations for rice and cassava in Indonesia. The inclusion of these dummy variables revealed surprisingly large differences in compensated price response across income groups. Although their results support the notion that poorer households respond differently to prices than the rich, the limitations of their data constrained them to consider only two foods and to specify changes in price response which are discontinuous with respect to income. I The formulation and estimation of the food demand equations is discussed in section II below. Section III presents the results of the estimation and discusses the nutritional implications of movements in relative food prices and other exogenous variables. Section IV summarizes our findings.

E MPIRICAL results reported in economics journals are selected from a large set of estimated models. Journals, through their editorial policies, engage in some selection, which in turn stimulates extensive model searching and prescreening by prospective authors. Since this process is well known to professional readers, the reported results are widely regarded to overstate the precision of the estimates, and probably to distort them as well. As a consequence, statistical analyses are either greatly discounted or completely ignored. This unfortunate equilibrium in the market for information is a result of the current econometric technology, which generates inferences only if a precisely defined model were available, and which can be used to explore the sensitivity of inferences only to discrete changes in assumptions. The reporting of a complete sensitivity analysis is ruled out therefore first, because the econometric theory which takes models as given would be rendered explicitly inadequate if the sensitivity analysis were reported, and, second, because the econometric technology, if used to explore sensitivity issues, would generate vast numbers of estimated models that journals are rightfully reluctant to print. It is the purpose of this article to discuss an alternative econometric technology that could increase the value of our profession's limited data resources. The basic assumption underlying this technology is that no econometric model can be taken as given. Because there are many models which could serve as a basis for a data analysis, there are many conflicting inferences which could be drawn from a given data set. If this fact of life is acknowledged, it deflects econometric theory from the traditional task of identifying the unique inferences implied by a specific model to the task of determining the range of inferences generated by a range of models. We propose that researchers be given the task of identifying interesting families of alternative models and be expected to summarize the range of inferences which are implied by each of the families. When a range of inferences is small enough to be useful and when the corresponding family of models is broad enough to be believable, we may conclude that these data yield useful information. When the range of inferences is too wide to be useful, and when the corresponding family of models is so narrow that it cannot credibly be reduced, then we must conclude that inferences from these data are too fragile to be useful. This contrasts greatly with the reporting schemes currently used by individuals. As a profession, however, we do suspend judgment on econometric results until they hold up to inspections by other researchers using other models. The advocacy process we use to accumulate professional opinion is therefore aimed in the same direction as our proposals, but the path we recommend is much more direct and the outcome is much more clearly stated. A simple introduction to this alternative econometric technology is given in section I of this paper. In writing this section we have attempted to communicate the main ideas as concisely as possible. As a consequence, there is no reference to any sophisticated statistical theory and especially no mention of the Reverend Thomas Bayes. For a more complete statement as well as theological fanfare, consult Leamer (1978). The proper test of our proposals is whether they are useful in practice. We believe that researchers will find them to be efficient tools for discovering the information in data sets and for communicating findings to the consuming public. In an effort to make clear the value of these techniques we present two examples in section II. These methods are not without their own problems, the most serious of which is their concentration on the point estimation problem and their neglect of hypothesis testing or interval estimation. The basic approach to studying and reporting the fragility of estimates which we describe in this paper can be readily extended to studying and reporting the fragility of t-values, though computational difficulties do arise. Received for publication June 15, 1981. Revision accepted for publication August 2, 1982. * University of California, Los Angeles, and Harvard University, respectively. Research supported by NSF Grant SOC78-09477. Comments of the referees have helped to improve both the content and the exposition. Thomas Wolff is thanked for able research assistance.

Many commentators believe that the phenomenon of urban sprawl, which is characterized by vigorous spatial expansion of urban areas, is a symptom of an economic system gone awry. By transforming pastoral farmland into often-unattractive suburbs, sprawl is thought to disrupt a natural balance between urban and non-urban land uses, leading to a deplorable degradation of the landscape.' This sentiment is often translated into policy through zoning restrictions designed to inhibit the conversion of land from agricultural to urban use (see Bryant and Conklin (1975)). The economist's view of urban expansion stands in stark contrast to this emotionally-charged indictment of sprawl. Economists believe that urban spatial size is determined by an orderly market process which correctly allocates land between urban and agricultural uses. The model underlying this view, which was originally developed by Muth (1969) and Mills (1972) and more completely analyzed by Wheaton (1974), suggests that urban spatial size is determined in a straightforward way by a number of exogenous variables. By showing empirically that urban size is related to the given variables (population, income, agricultural rent, and commuting cost) in the manner predicted by the model, the present paper achieves two goals. First, the empirical results suggest that the economist's view of urban sprawl is justified: rather than being determined by a process which indiscriminately consumes agricultural land, urban sizes are the result of an orderly market equilibrium where competing claims to the land are appropriately balanced.2 Second, by confirming the urban size predictions of the underlying model, the empirical results constitute yet another piece of evidence validating the basic framework of urban economic analysis.3 The plan of the paper is as follows. Section II sketches the structure of the Muth-Mills model and presents the main comparative static results relevant to urban sprawl. With the model's predictions in focus, section III discusses the sample and the data, and section IV presents the empirical results. Section V offers conclusions.