COLLEGE-TO-WORK MIGRATION OF TECHNOLOGY GRADUATES AND HOLDERS OF DOCTORATES WITHIN THE UNITED STATES

ABSTRACT.  This study estimates a series of random parameter logit models of the college-to-work migration decisions of technology graduates and holders of doctorates within the United States. We employ detailed information on the migration-relevant characteristics of individuals, as well as on their actual origins and destinations at the metropolitan scale. In addition to its obvious implications for "brain drain" policies in U.S. metropolitan areas, the study demonstrates the richness of the random parameters technique for behavioral-geographic analysis. We find that science and technology graduates migrate to better educated places, other things equal; that PhD graduates pay greater attention to amenity characteristics than other degree holders; and that foreign students from some immigrant groups migrate to places where those groups are concentrated.     

Estimating the Marginal Willingness to Pay for Commuting

With informational frictions on the labor market, hedonic wage regressions provide biased estimates of the willingness to pay for job attributes. We show that a recent theoretical result, which states that the variation in job durations provides a basis for obtaining good estimates, can be generalized to a wide class of search models. We apply this result by estimating the marginal willingness of employed workers to pay for commuting, using Dutch longitudinal data. The average willingness to pay for one hour commuting is estimated to equal almost half of the hourly wage rate.     

Parameter mixing errors within a measuring volume with applications to incoherent scatter

The effect on parameter error estimates resulting from parameter variations within the measuring volume under consideration is studied in the framework of linear statistical inversion theory. It is shown that using estimates for the parameter averages is equivalent to having the theory corrected by the covariances of the variables coupled with the second derivatives of the theory function. If the parameter distributions were known exactly, this would only introduce a bias in the linear theory and hence a systematic error in the parameter centre point estimates. When the distributions are not known exactly, there is another source of error consisting of the uncertainties in the parameter variation estimates. This leads to new error bounds on the allowed parameter variability within the volume under consideration if some prescribed accuracy in the parameter average estimates is required. These considerations are applied to incoherent scatter (IS) radar measurements, where it is important to be able to estimate the effect of integrating both in space and time over a volume with varying parameters in order to obtain spectra or autocorrelation functions. Numerical examples are given in the case of the O⁺ content estimates in measurements with the EISCAT UHF radar, when for example the ion temperature varies over the integration ranges. The results obtained may be used in the design of experiments when high resolution composition measurements are required.     

GRAVITY AND SPATIAL STRUCTURE: THE CASE OF INTERSTATE MIGRATION IN MEXICO*

ABSTRACT The estimation of gravity models of internal (aggregate) place‐to‐place migration is plagued with endogeneity (omitted‐variable) biases if the unobserved effects of spatial structure are not accounted for. To address this econometric problem, this paper presents a more general specification of the gravity model, which allows for (bilateral) parameter heterogeneity across individual migration paths—along with (unilateral) origin‐ and destination‐specific effects. The resultant “three‐way fixed‐effects” (3FE) model is applied for an analysis of interstate migration in Mexico based on cross‐sectional data. To overcome parameter‐dimensionality problems (due to limited or incomplete information), the 3FE model is estimated using the Generalized Maximum Entropy (GME) estimator. The empirical implications of this new modeling strategy are illustrated by contrasting the 3FE‐GME estimates with those for the traditional and two‐way fixed‐effects (2FE) models. The former are far more plausible and intuitively interpretable than their traditional and 2FE counterparts, with parameter estimates changing in expected directions. The (average) effect of the migrant stock is markedly smaller than usually estimated, providing a more realistic measure of network‐induced migration. Migration outflows from centrally located origins have significantly steeper distance decay. Path‐specific distance effects exhibit directional asymmetries and spatial similarities.     

Tree Densities Last Century on the Lowland Gippsland Plain,Victoria

Tree densities in the mid 1800s were calculated for 16 areas on the lowland Gippsland plain, Victoria, using data on historical maps. The plotless, closest individual method was used on map data, which listed the distance and compass bearings of trees from allotment corners. Densities ranged from 2 to 59 trees per hectare, with most estimates below 30 trees per hectare. Sparsest trees were in and near areas mapped as ‘open plains’ and the densest tree cover was on seasonally flooded river flats. Whilst it seems prudent to treat such figures as indicative rather than precise, this simple method holds considerable promise for obtaining quantitative estimates of tree densities before widespread clearing.     

Using Simple Genetic Algorithms to Calibrate Spatial Interaction Models

The paper investigates the use of two genetic algorithms in an attempt to obtain globally optimal parameter estimates for a mix of simple and complex spatial interaction models. The genetic algorithms work well and are strongly advocated as a more robust approach particularly for use with the more complex multiparameter models where the differences in both performance and parameter values are judged to be significant.     

云南少数民族获食模式探讨

获食模式的差异源于人类对不同生态环境的适应。云南少数民族获食模式的多样性,既是各民族对当地生态环境适应的结果,也是各民族饮食结构差异的主要原因,同时反映出云南各少数民族经济社会发展的不平衡性和文化的多样性。本文根据自然环境和生产方式的差异,把云南少数民族的获食模式分为高山峡谷农牧型、刀耕火种-狩猎采集型、山坡梯田灌溉农耕型、河谷盆地灌溉精耕型等类型,并从文化生态学的角度对其地域分布、类型特征、形成原因等进行了分析。     

OBTAINING PROBABILISTIC ESTIMATES OF DISPLACEMENT ON A LANDSLIDE DURING FUTURE EARTHQUAKES

The assessment of earthquake triggered landslide hazard may be undertaken using both deterministic and probabilistic techniques. Probabilistic methods have been developed because much of the data can be considered as random variables where parameters such as the angle of internal friction and moisture content do not have a single fixed value but may assume any number of values across a range. This random variability can be modelled by a probability density function (PDF) which describes the relative likeli-hood that a random variable will assume a particular value. Instead of using just the average or expected value of an input parameter, the complete range of possible values can be used to estimate a range of possible outcomes. Thus the probability of a slope being unstable can be obtained rather than a single indicator of stability. Such proba-bilistic analyses allow for the incorporation of the likely variability of each parameter and therefore allow a more intimate assessment of slope stability to be derived. Utilising empirical relationships for calculating earthquake ground motions and associated slope displacement, an investigation was undertaken to identify the contribution that modern simulation techniques could make to the assessment of earthquake-triggered landslides. To achieve this, geotechnical and earthquake data obtained from a deep-seated landslide triggered during the M _w 7.0 Loma Prieta earthquake was used. By incorporating the variability of the geotechnical parameters and the uncertainty in earthquake location the model derived the probabilities associated with increasing amounts of slope displacement during future probable earthquakes. Analysis was undertaken for four of the principal fault segments in the San Francisco Bay area. These estimates were then combined with the occurrence probabilities of the earthquakes to provide temporal estimates of dis-placement for a 30 year period. Results indicated that a M _w 7.0 earthquake located on the Peninsula Segment of the San Andreas fault was most hazardous with a 11% chance of minor slope displacement (≥0.10 m) and a 6% chance of moderate slope displacement (≥0.30 m) within the next 30 years.     

Empirical Zoning Distributions for Small Area Data

It is well established that using data summaries for a set of geographic areas or zones to estimate the parameters of a statistical model, commonly called ecological inference, frequently leads to the modifiable area unit problem (MAUP). In this article, the zoning effect of the MAUP is investigated for a range of scales. A zoning distribution is defined, and then used to characterize the zoning effect for parameter estimates from ecological analyses. Zone‐independent parameter estimates are obtained using the mean of the zoning distribution, and assessed using the variance of the zoning distribution. Zoning distributions are illustrated for parameter estimates from two ecological regression models at multiple scales using Australian National Health Survey data. For both a continuous response variable and a binary response variable, the empirical zoning distributions are unimodal, relatively symmetrical with appreciable variation, even when based on a large number of zones. The “ecological mean,” or expected value of the empirical zoning distribution at each scale, displays systematic variation with scale and the zoning distribution variance also depends on scale. The results demonstrate that the zoning effect should not be ignored, and the sensitivity of ecological analysis results to the analysis zones should be assessed.     

Quenching the Thirst: The Cost of Water in Fragile Environments

Public policy has often addressed the problems of water supply and sanitation from the supply side to the neglect of demand side aspects in developing countries like India. This policy has not only rendered a large number of projects financially unviable but has also resulted in inadequate coverage of aspects such as population and ecological unsustainability. This article, based on household level information from six villages in a water scarce region of India (Rajasthan state), examines inter- and intra-village variations in water use and the costs, direct and indirect, involved in obtaining water. It also estimates households' willingness and ability to pay for water, using the contingent valuation method (CVM). Using qualitative as well as quantitative methods, it is argued that it is the failure of government policy and of institutions which has led to severe water shortages in harsh environments rather than supply or financial bottlenecks per se. While the estimates of price elasticity of water use indicate the feasibility of water pricing in the rural areas, the willingness to pay estimates question the general assumption that rural households are willing to pay 5 per cent of their income/expenditure for water. Various economic and extra economic factors such as household income, low opportunity costs of women and children, and attitudes towards female labour and public goods are vital in influencing the households' willingness to pay for water.     

CHILDHOOD DIET: A CLOSER EXAMINATION OF THE EVIDENCE FROM DENTAL TISSUES USING STABLE ISOTOPE ANALYSIS OF INCREMENTAL HUMAN DENTINE*

Incremental dentine analysis utilizes tissue that does not remodel and that permits comparison, at the same age, of those who survived infancy with those who did not at high temporal resolution. Here, we present a pilot study of teeth from a 19th‐century cemetery in London, comparing the merits of two methods of obtaining dentine increments for subsequent isotope determination. Covariation in δ¹³C and δ¹⁵N values suggests that even small variations have a physiological basis. We show that high‐resolution intra‐dentine isotope profiles can pinpoint short‐duration events such as dietary change or nutritional deprivation in the juvenile years of life.     

A Comparison of Spatially Varying Regression Coefficient Estimates Using Geographically Weighted and Spatial‐Filter‐Based Techniques

Geographically weighted regression (GWR) is a technique that explores spatial nonstationarity in data‐generating processes by allowing regression coefficients to vary spatially. It is a widely applied technique across domains because it is intuitive and conforms to the well‐understood framework of regression. An alternative method to GWR that has been suggested is spatial filtering, which it has been argued provides a superior alternative to GWR by producing spatially varying regression coefficients that are not correlated with each other and which display less spatial autocorrelation. It is, therefore, worthwhile to examine these claims by comparing the output from both methods. We do this by using simulated data that represent two sets of spatially varying processes and examining how well both techniques replicate the known local parameter values. The article finds no support that spatial filtering produces local parameter estimates with superior properties. The results indicate that the original spatial filtering specification is prone to overfitting and is generally inferior to GWR, while an alternative specification that minimizes the mean square error (MSE) of coefficient estimates produces results that are similar to GWR. However, since we generally do not know the true coefficients, the MSE minimizing specification is impractical for applied research.     

Bayesian Estimation of Regional Production for CGE Modeling

Abstract Computable general equilibrium (CGE) models are often criticized for using restrictive functional forms and relying on external sources for parameter values in their calibration. CGE modelers argue that in many instances reliable econometric estimates of important model parameters are unavailable because they must be estimated using small numbers of time‐series observations. To address these criticisms, this paper uses a Bayesian approach to estimate the parameters of a translog production function in a regional computable general equilibrium model. Using priors from more reliable national estimates, and parameter restrictions required by neoclassical production theory, estimation is done by Markov chain Monte Carlo simulation. A stylized regional CGE model is then used to contrast policy responses of a Cobb‐Douglas specification with those from the estimated translog equation.     

Interpretation of elevation-scan HF backscatter data from Losquet Island radar

Most methods using HF ground backscatter radar data to estimate the ionospheric bottomside electron density profile rely upon multi-frequency measurements of the minimum group delay. However, information of the same nature can also be extracted at a single frequency if the elevation angle can be precisely controlled. We outline the analysis of this technique, known as elevation-scan backscatter sounding. The relevant parameter estimation problem is studied using a Bayesian approach. We report on an experiment using the Losquet Island radar to illustrate this method. The performance is compared to ionosonde data. This technique provides a method of teledetection of the bottomside F-region electron density profile hundreds of km from the radar site: however, further development is needed to provide increased reliability of the estimates.     

THE DETERMINANTS OF LOCALIZATION AND URBANIZATION ECONOMIES: EVIDENCE FROM THE LOCATION OF NEW FIRMS IN SPAIN

The objective of this paper is to analyze why firms in some industries locate in specialized economic environments (localization economies) while those in other industries prefer large city locations (urbanization economies). To this end, we examine the location decisions of new manufacturing firms in Spain at the city level and for narrowly defined industries. First, we estimate firm location models to obtain estimates that reflect the importance of localization and urbanization economies in each industry. Then, we regress these estimates on industry characteristics related to the potential importance of labor market pooling, input sharing, and knowledge spillovers. Urbanization effects are high in knowledge‐intensive industries, suggesting that firms locate in large cities to benefit from knowledge spillovers. We also find that localization effects are high in industries that employ workers whose skills are more industry‐specific, suggesting that industries locate in specialized economic environments to share a common pool of specialized workers.     

THE EFFECTS OF AGGLOMERATION ON WAGES: EVIDENCE FROM THE MICRO‐LEVEL

This paper estimates individual wage equations to test two rival non‐nested theories of economic agglomeration, namely New Economic Geography (NEG), as represented by the NEG wage equation and urban economic (UE) theory, in which wages relate to employment density. In the U.K. context, we find that for male respondents, there is no significant evidence that wage levels are an outcome of the mechanisms suggested by NEG or UE theory, but this is not the case for female respondents. We speculate on the reasons for the gender difference.     

An Area‐Based Approach for Estimating Extreme Precipitation Probability

Accurate estimates of heavy rainfall probabilities reduce loss of life, property, and infrastructure failure resulting from flooding. NOAA's Atlas‐14 provides point‐based precipitation exceedance probability estimates for a range of durations and recurrence intervals. While it has been used as an engineering reference, Atlas‐14 does not provide direct estimates of areal rainfall totals which provide a better predictor of flooding that leads to infrastructure failure, and more relevant input for storm water or hydrologic modeling. This study produces heavy precipitation exceedance probability estimates based on basin‐level precipitation totals. We adapted a Generalized Extreme Value distribution to estimate Intensity‐Duration‐Frequency curves from annual maximum totals. The method exploits a high‐resolution precipitation data set and uses a bootstrapping approach to borrow spatially across homogeneous regions, substituting space in lieu of long‐time series. We compared area‐based estimates of 1‐, 2‐, and 4‐day annual maximum total probabilities against point‐based estimates at rain gauges within watersheds impacted by five recent extraordinary precipitation and flooding events. We found considerable differences between point‐based and area‐based estimates. It suggests that caveats are needed when using pointed‐based estimates to represent areal estimates as model inputs for the purpose of storm water management and flood risk assessment.     

THE SHORT-RUN AND LONG-RUN FACTOR-MARKET CONSEQUENCES OF IMMIGRATION TO THE UNITED STATES*

ABSTRACT. This paper applies the production-theory approach to assess the impact on domestic wages and employment of immigration to the United States. Inputs are disaggregated between recent immigrants, non-recent immigrants, native workers, and capital. Census cross-sectional data for 1980 and for 123 metropolitan areas are used. Empirical estimates are reported for alternative functional forms with special attention devoted to required curvature conditions which have frequently been violated in previous work. Elasticity estimates are reported for alternative settings, including for the short run where we view domestic factor prices as given and the long run where we treat them as flexible.     

MAXIMUM LIKELIHOOD ESTIMATION OF GRAVITY MODEL PARAMETERS

ABSTRACT. It is shown that, under some very mild conditions, maximum likelihood estimates of gravity model parameters exist and are unique (up to a scale transformation for some parameters). An algorithm for finding such estimates is also proposed.