Freedom and gross in-migration: an empirical study of the post-great recession experience

Determinants of migration, including policy variables such as tax rates, have been extensively studied by regional scientists over the past several decades. The development of the Economic Freedom of North America Index has allowed researchers to test the relationship between migration patterns and economic freedom, with recent studies finding that net in-migration is positively related to economic freedom. Using a new cross-section measure of economic and personal freedom at the state level, we investigate the relationship between gross in-migration and economic freedom on the one hand and then between gross in-migration and total freedom on the other hand. This empirical study of domestic U.S. migration during the post-Great Recession period finds clear evidence that migrants prefer to move to those states affording higher levels of economic freedom and higher levels of total freedom.     

Using difference equations to find optimal tax structures on the SugarScape

The use of equations to describe agent-based model dynamics allows access to mathematical theory that is not otherwise available. In particular, equation models can be effective at solving optimization problems—that is, problems concerning how an agent-based model can be most effectively steered into a particular state. In order to illustrate this strategy, we describe a modified version of the well-known SugarScape model and implement taxation. The optimization problem is to determine tax structures that minimize deaths but maximize tax income. Tax rates are dependent upon the amount of sugar available in a particular region; the rates change over time. A system of discrete difference equations is built to capture agent-based model dynamics. The equations are shown to capture the dynamics very well both with and without taxation. A multi-objective optimization technique known as Pareto optimization is then used to solve the problem. Rather than focusing on a cost function in which the two objectives are assigned weights, Pareto optimization is a heuristic method that determines a suite of solutions, each of which is optimal depending on the priorities of the researcher. In this case, Pareto optimization allows analysis of the tradeoff between taxes collected and deaths caused by taxation. The strategies contained here serve as a framework for a broad class of models.     

A dymimic model of housing price determination

This paper presents and estimates a model of the resale housing market. The data are a cross-section of monthly time series obtained from the multiple-listing service for a suburb of San Diego. The model is specified and estimated as a dynamic multiple indicator multiple cause system of equations where the capitalization rate is taken to be an unobservable time series to be estimated jointly with the unknown parameters. These are estimated by maximum likelihood using an EM algorithm based upon Kalman filtering and smoothing.The specification of the model features hedonic equations for each house sale and a dynamic equation for the capitalization rate which is constrained to make the expectation of prices equal the present value of the net returns to home ownership whenever the economic variables stabilize at steady state values. Out of steady state, the capitalization rate slowly adapts to new information.The model attributes a large portion of housing price increases of the 1970's to a fall in the capitalization rate which in turn was driven by rental inflation, tax rates and mortgage rates. Post-sample simulations indicate an initial flattening of housing inflation rates and later a fall brought on by the increase in steady state capitalization rates. In-sample simulations show that although both Proposition 13 and the inflation induced rise in the marginal income tax rates provided partial explanations for the fall in capitalization rates, the single most important factor was the acceleration in price of housing services which interacted with the tax treatment of home ownership to produce an amazing 18% average annual rate of price increase over the last seven years of the 1970's.     

Missing Pieces in Ecosystem Restoration: The Case of the Florida Everglades

The largest ecosystem restoration in the world-a $7.8 billion rescue package-is now beginning in the Florida Everglades. This paper examines both the economic impact of the restoration itself and those pieces that are 'missing' from the official project analysis; namely, increased tourism, urban construction, in-migration, and changing agricultural patterns. These pieces comprise a variety of scenarios that are tested for a 45 year planning period with an augmented input-output model derived from a regional SAM. The new output and employment generated by the 'missing pieces', which are small relative to the vast economic base of the region, do represent a considerable increase over the annual growth, especially by the year 2045. We conclude with a discussion of ways in which a growing regional economy might be reconciled with ecosystem restoration.     

The Influence of Geography on the Spatial Agglomeration of Production in the European Union

Abstract

Small regions and towns often experience problems such as high out-migration and unemployment. In these situations there is an urgent need to do something positive. Infrastructure development projects, partially financed by the national government, are a popular suggestion. We ponder the relevance of these actions in this paper in a context of project evaluation. We introduce computable general equilibrium (CGE) modelling as a complement of the other quantitative evaluation techniques. We will use the town of Lapua in South Ostrobothnia, Finland, which is planning to implement two large-scale infrastructure projects, as an example. Our simulation tool is the Finnish multi-sector and interregional CGE RegFin model. We consider the regional short-run effects of the construction phase, the long-run effects of new business activity and the so-called secondary effects based on the commuting and trade patterns of the households.     

Aggregate Investment in South Africa: A Model with Implications for Political Reform

A small macroeconomic model is used as the basis for estimating the determinants of investment in South Africa within a simultaneous equations framework. Investment is highly sensitive to interest rates, relative prices and political instability. The policy implications of such sensitivity are outlined.     

A multipurpose multilevel socio economic planning model: Theoretical framework and preliminary results

The authors specify a time series and cross section model which consists of 20 reduced form equations consisting of 64 socioeconomic variables for which data are available at the U.S.A. county level. The design of a model at this level of detail permits analysis at the multicounty level for regions and states and is also applicable for nations where socioeconomic data files are not plentiful. In addition to the multilevel geographic applicability of the model, it consists of variables measured in terms of growth rates so that intersectoral consistency checks can be integrated in the development of policy sensitive applications of the model. Finally, the model consists of a series of sector by sector equations to facilitate policy tests and to simplify the simultaneity requirements of the model. Preliminary results are presented for the State of Maryland and its 24 counties.     

Desired and actual labour supply of unmarried men and women in the Netherlands

Desired and actual working hours of unmarried adults are analyzed. A discrete structural neoclassical model is used to explain desired hours, which depend on gross wage rates, tax and benefit rules, other income, and some background variables. The model takes account of fixed costs of working and of prediction errors in wage rates of nonworkers. Actual hours are explained from desired hours and hours restrictions. Deviations between actual and desired hours are used to identify equations for involuntary unemployment and the lack of part-time jobs. The model is estimated using cross-section data from the Dutch Socio-Economic Panel. We find larger wage elasticities of desired hours of work for women than for men. Involuntary unemployment and a lack of part-time jobs appear to be important sources of hours restrictions. Individuals with (potential) wages below the minimum wage have a significantly larger probability of involuntary unemployment than others.     

Effective Rates of Sectoral Productivity Change

In effective rates of sectoral productivity change, some of the inputs are treated as produced. Here, this is extended to cover all the inputs. All the sectoral rates of productivity growth based on a static input–output (IO) framework are shown to be equal to the corresponding rates of decrease in the production price. For the direct rate, all the input prices are treated as exogenous constants. For the effective rates, prices of the inputs, which are treated as produced, are determined by production technology. The fully effective rate is derived from the price equations of the closed dynamic IO model. It is equal to the rate of decrease in the production price when the prices of all inputs, human capital and human time included, depend on production technology. The overall rate, obtained as a weighted sum of the fully effective sectoral rates, is equal to the rate of growth in the growth potential of the economy.     

State and County Incarceration Rates:

ABSTRACT This study examines the direct and indirect effects of race and income inequality on imprisonment rates across states. The analysis is designed to: 1) investigate whether race and income inequality are significantly related to imprisonment when controlling for crime , 2) assess the relative magnitudes of the direct and indirect effects; and 3) assess the relative magnitudes of race and income inequality. Crime is found to be the strongest predictor of incarceration rates in five of the six equations estimated. Income inequality is significantly related to incarceration rates in two of the six equations. There was no clear evidence of a direct race effect. The indirect effect of race was greater than the direct effect in four of the six equations.     

Stochastic differential equation modeling the prevalence of rare chronic diseases with an application to systemic lupus erythematosus

In this article we describe a system of stochastic differential equations to model the age‐specific prevalence of rare chronic diseases from incidence and mortality rates. As an application, the age profile of the prevalence of systemic lupus erythematosus in England and Wales in1995 is calculated. The results are in good agreement with the observed epidemiological measures.     

The specification and estimation of interrelated factor demands under uncertainty

This paper studies a model of the firm's interrelated demands for the factors of production incorporating exogenous variables with uncertain future values, multiple quasi-fixed factors, depreciation in use, and non-symmetric internal costs of adjustment. The inputs considered are production labor, non-production workers, capital, inventories of non-finished goods, and capacity and non-production worker utilization rates. A simultaneous system of factor demand equations with constraints is estimated and using U.S. manufacturing data. The model is shown to be tractable under certain assumptions. The results are encouraging given the complexity and the nature of the model.     

Voting with their feet: Relative economic conditions and state migration patterns

Over the past decade, state and local policymakers and business leaders across the U.S. have expressed concern regarding the ability to attract and retain skilled workers, given the economic climate of their states compared with other parts of the nation. Examining the factors underlying state-level migration trends is important to determine what role, if any, public policy might play in addressing their potential impact on local labor supply. Using data from the Internal Revenue Service for each of the 48 states in the continental United States from 1977 through 2006, this paper examines the role of three economic factors—namely labor market conditions, per capita incomes, and housing affordability—in determining domestic state-to-state migration flows. Estimates from a logistic model of out-migration show that while all three measures of relative economic conditions are significant determinants of migration, the magnitude of their impact varies and has changed considerably over time. For example, the importance of per capita income as a determining factor has fallen considerably since the late 1970s, while that of housing affordability has risen. Interestingly, the role of labor market conditions—while significant throughout the entire 30-year period—was most prominent in the late 1980s and early 1990s. Estimates from the model are used to forecast migration for 2009 for selected states. The results from this exercise are surprisingly accurate when compared to actual state migration patterns for that year.     

The Economic Effects of Right to Work Laws

Right to work (RTW) laws have had growing labor market importance, as the proportion of Americans living in RTW states has risen over time, mainly because of a large in-migration of labor and capital. In the 2000–2009 period alone, over 5 million Americans moved into RTW states from non-RTW jurisdictions. This resource movement has led to greater output growth in RTW states. Controlling for other factors, it appears RTW is positively associated with rising income per capita as well, and arguably an improved quality of life if migration statistics are any indicator. The long term political equilibrium that has led to little change over time in the adoption of RTW laws could end as pro-RTW forces gain political clout relative to their union opponents.     

INTERNAL MIGRATION IN TURKEY, 1965–1985: TEST OF CONFLICTING FINDINGS IN THE LITERATURE

The purpose of this paper is to bring new insights to some of the conflicting findings in the migration literature about developing countries by using detailed analyses of Turkish migration data. The possible reasons behind inconsistencies in the findings are explained in terms of spatial and temporal characteristics of the data, and by national macro factors (mainly the level of urbanization and the characteristics of the urban systems). Tested were rural out-migration and push factors; changes in the size of rural-to-urban and urban-to-rural return migration; the effect of distance; and the share and effect of rural-to-urban migration in the urban growth and in the unbalanced population distribution in developing countries.     

Exclusionary policies in urban development: Under-servicing migrant households in Brazilian cities

Localities in developed countries often enact regulations to deter low-income households from moving in. In developing countries, such restrictions lead to the emergence of informal housing sectors. To deter low-income migrants, localities in developing countries withhold public services to the informal housing sector. Using a large sample of Brazilian localities, we examine migration and exclusion, focusing on the public provision of water to small houses where low-income migrants are likely to live. Withholding water connections reduces the locality growth rate, particularly of low-education households. In terms of service provision, during dictatorship in Brazil, we find evidence of strategic exclusion, where localities appear to withhold services to deter in-migration. We also find evidence of strategic interactions among localities within metro areas in their setting of service levels: if one locality provides more services to migrant households, other localities respond by withholding service.     

A microeconomic planning model for the new york times newspaper

The New York Times model is a large-scale model which forecasts sales and earnings for the New York Times newspaper. Sturcturally, it is composed of two major blocks; a demand module, and a production, cost and revenue module. The demand module, the heart of the model, is a set of simultaneous nonlinear econometric equations which forecast physical volume, approximately 35 categories of advertising lines and 10 categories of circulation. The second block is recursive and contains roughly 300 equations, some of which are stochastic behavioral equations. This block converts the volume forecasts into paging, newsprint consumption, newsprint distribution and manning requirements. These physical flows are then monetized, using price and wage forecasts, to produce estimates of revenue, fixed and variable costs, and operating profit. This paper summarizes the development of the model, with emphasis on the advertising and circulation model. It should be noted that the structure of the model is constantly evolving. Consequently, emphasis is placed on the conceptual underpinnings of the model not on a detailed presentation of the current structure.     

Price adjustment and market structure: A single-industry study

The administered price hypothesis of Gardnier Means has continued to attract a great deal of empirical attention. Unfortunately, the results of all this research have not been consistent. The present paper tries to circumvent the usual empirical difficulties by using a lagged adjustment model for a single industry with geographically separate markets. It examines the rate of price adjustment and the frequency of price changes for newspaper advertising rates for a sample of local papers in Ireland. Adjustment equations are run for each newspaper using labour and materials cost indices as explanatory variables. The partial adjustment coefficient estimates are then related to market structure and firm specific characteristics.     

Assembly information modelling and sequences generation algorithm of autobody

This paper attempts to formalise the assembly information of autobody and solve all feasible assembly sequences. In this paper, an assembly information model is built by using polychromatic sets and the mathematic forms of these models are given. The model is described by locating relation equations which express the constrained relationship of locating and displacement interference equations which express the constrained relationship of possible displacement. At first, the assembly information model is used to model the assembly information of autobody; then according to locating relation equations and displacement interference equations, all feasible assembly sequences can be derived. Finally, a case study illustrates the application of the proposed assembly information model. The proposed assembly information model and sequences generation approach is successfully demonstrated by autobody assembly planning, and could facilitate assembly sequence optimisation under a robust and reliable situation.