Some Identification Issues in Nonparametric Linear Models with Endogenous Regressors

In applied work economists often seek to relate a given response variable y to some causal parameter mu* associated with it. This parameter usually represents a summarization based on some explanatory variables of the distribution of y, such as a regression function, and treating it as a conditional expectation is central to its identification and estimation. However, the interpretation of mu* as a conditional expectation breaks down if some or all of the explanatory variables are endogenous. This is not a problem when mu* is modelled as a parametric function of explanatory variables because it is well known how instrumental variables techniques can be used to identify and estimate mu*. In contrast, handling endogenous regressors in nonparametric models, where mu* is regarded as fully unknown, presents di±cult theoretical and practical challenges. In this paper we consider an endogenous nonparametric model based on a conditional moment restriction. We investigate identification related properties of this model when the unknown function mu* belongs to a linear space. We also investigate underidentification of mu* along with the identification of its linear functionals. Several examples are provided in order to develop intuition about identification and estimation for endogenous nonparametric regression and related models.

Efficiency Bounds for Estimating Linear Functionals of Nonparametric Regression Models with Endogenous Regressors

Consider a nonparametric regression model Y=mu*(X) + e, where the explanatory variables X are endogenous and e satisfies the conditional moment restriction E[e|W]=0 w.p.1 for instrumental variables W. It is well known that in these models the structural parameter mu* is 'ill-posed' in the sense that the function mapping the data to mu* is not continuous. In this paper, we derive the efficiency bounds for estimating linear functionals E[p(X)mu*(X)] and int_{supp(X)}p(x)mu*(x)dx, where p is a known weight function and supp(X) the support of X, without assuming mu* to be well-posed or even identified.

The Value of Waiting: Foreign Direct Investment with Uncertainty and Imperfect Local Knowledge

This paper examines the role of uncertainty and imperfect local knowledge in foreign direct investment. The main idea comes from the literature on investment under uncertainty, such as Pindyck (1991) and Dixit and Pindyck (1994). We empirically test .the value of waiting. with a dataset on foreign direct investment (FDI). Many factors (e.g., political and economic regulations) as well as uncertainty and the risks due to imperfect local knowledge, determine the attractiveness of FDI. The uncertainty and irreversibility of FDI links the time interval between permission and actual execution of such FDI with explanatory variables, including information on foreign (home) countries and domestic industries. Common factors, such as regulatory change and external shocks, may affect the uncertainty when foreign investors make irreversible FDI decisions. We derive testable hypotheses from models of investment under uncertainty to determine those possible factors that induce delays in FDI, using Korean data over 1962 to 2001.

A Bootstrap-Regression Procedure to Capture Unit Specific Effects in Data Envelopment Analysis

The Data Envelopment Analysis (DEA) efficiency score obtained for an individual firm is a point estimate without any confidence interval around it. In recent years, researchers have resorted to bootstrapping in order to generate empirical distributions of efficiency scores. This procedure assumes that all firms have the same probability of getting an efficiency score from any specified interval within the [0,1] range. We propose a bootstrap procedure that empirically generates the conditional distribution of efficiency for each individual firm given systematic factors that influence its efficiency. Instead of resampling directly from the pooled DEA scores, we first regress these scores on a set of explanatory variables not included at the DEA stage and bootstrap the residuals from this regression. These pseudo-efficiency scores incorporate the systematic effects of unit-specific factors along with the contribution of the randomly drawn residual. Data from the U.S. airline industry are utilized in an empirical application.

Modeling survival and the development of second primary tumors among Hodgkin's disease patients

Hodgkin's disease (HD) is a cancer of the lymphatic system. Survivors of HD face varieties of consequent adverse effects, in which secondary primary tumors (SPT) is one of the most serious consequences. This dissertation is aimed to model time-to-SPT in the presence of death and HD relapses during follow-up.^ The model is designed to handle a mixture phenomenon of SPT and the influence of death. Relapses of HD are adjusted as a covariate. Proportional hazards framework is used to define SPT intensity function, which includes an exponential term to estimate explanatory variables. Death as a competing risk is considered according to different scenarios, depending on which terminal event comes first. Newton-Raphson method is used to estimate the parameter estimates in the end.^ The proposed method is applied to a real data set containing a group of HD patients. Several risk factors for the development of SPT are identified and the findings are noteworthy in the development of healthcare guidelines that may lead to the early detection or prevention of SPT.^

A STUDY OF THE RELATIONSHIP BETWEEN SELF-ASSESSMENT AND CLINICAL EVALUATION OF HEARING STATUS

The relationship was explored between a subjective measure of hearing status, derived from a functional self-assessment expressed in terms of ability to hear and understand spoken words, and a comparable objective measure of hearing status, obtained from a speech reception test. The Augmentation Survey of the Health and Nutrition Examination Survey of the National Center for Health Statistics provided the necessary data for a sample of 3059 adults. Using chi-square tests for the subsample with the highest level of objectively assessed hearing status, favorable subjective assessments were found to be significantly associated with higher income, lower age group, higher level of educational attainment, greater psychological adjustment, fewer symptoms of depression, and higher self-ratings of overall health. In a linear regression with self-assessment of hearing status as the dependent variable, less than one-quarter of the variation could be explained by objective status and the six explanatory variables.^

A comparative state policy analysis of the adoption of birth defects surveillance legislation

Birth defects are the leading cause of infant mortality in the United States and are a major cause of lifetime disability. However, efforts to understand their causes have been hampered by a lack of population-specific data. During 1990–2004, 22 state legislatures responded to this need by proposing birth defects surveillance legislation (BDSL). The contrast between these states and those that did not pass BDSL provides an opportunity to better understand conditions associated with US public health policy diffusion. ^ This study identifies key state-specific determinants that predict: (1) the introduction of birth defects surveillance legislation (BDSL) onto states' formal legislative agenda, and (2) the successful adoption of these laws. Secondary aims were to interpret these findings in a theoretically sound framework and to incorporate evidence from three analytical approaches. ^ The study begins with a comparative case study of Texas and Oregon (states with divergent BDSL outcomes), including a review of historical documentation and content analysis of key informant interviews. After selecting and operationalizing explanatory variables suggested by the case study, Qualitative Comparative Analysis (QCA) was applied to publically available data to describe important patterns of variation among 37 states. Results from logistic regression were compared to determine whether the two methods produced consistent findings. ^ Themes emerging from the comparative case study included differing budgetary conditions and the significance of relationships within policy issue networks. However, the QCA and statistical analysis pointed to the importance of political parties and contrasting societal contexts. Notably, state policies that allow greater access to citizen-driven ballot initiatives were consistently associated with lower likelihood of introducing BDSL. ^ Methodologically, these results indicate that a case study approach, while important for eliciting valuable context-specific detail, may fail to detect the influence of overarching, systemic variables, such as party competition. However, QCA and statistical analyses were limited by a lack of existing data to operationalize policy issue networks, and thus may have downplayed the impact of personal interactions. ^ This study contributes to the field of health policy studies in three ways. First, it emphasizes the importance of collegial and consistent relationships among policy issue network members. Second, it calls attention to political party systems in predicting policy outcomes. Finally, a novel approach to interpreting state data in a theoretically significant manner (QCA) has been demonstrated.^

Colorectal cancer screening: Participation and determinants in West Texas

Early detection by screening is the key to colorectal cancer control. However, colorectal cancer screening and its determinants in rural areas have not been adequately studied. This goal of this study was to investigate the screening participation and determinants of colonoscopy, sigmoidoscopy, and/or fecal occult blood test (FOBT) in subjects of Project Frontier from the rural counties of Cochran, Bailey and Parmer, Texas. Subjects ( n=820 with 435 Hispanics, 355 Non-Hispanic Whites, 26 African Americans, and 4 unknown ethnicity; 255 males, 565 females, aged from 40 to 92 years) were from Project FRONTIER. Stepwise logistic regression analysis was performed. Explanatory variables included ethnicity (Hispanic, Non-Hispanic white and African American), gender, health insurance, smoking status, household income, education (years), physical activity, overweight, other health screenings, personal physicians, family history (first-degree relatives) of cancers, and preferred language (English vs. Spanish) for interview/testing. The screening percentage for ever having had a colonoscopy/sigmoidoscopy (51.8%) in this cohort aged 50 years or older is well below the percentage of the nation (65.2%) and Texas (64.6%) while the percentage for FOBT (29.2%) is higher than in the nation (17.2%) and Texas (14.9%). However, Hispanics had significantly lower participation than non-Hispanic whites for colonoscopy/sigmoidoscopy (37.0% vs. 66.0%) and FOBT (16.5% vs. 41.7%), respectively. Stepwise logistic regression showed that predictors for colonoscopy, sigmoidoscopy or FOBT included Hispanic race (p = 0.0045), age (p < 0.0001), other screening procedure (p < 0.0001), insurance status (p < 0.0001) and physician status (p = 0.0053). Screening percentage for colonoscopy/sigmoidoscopy in this rural cohort is well below the national and Texas level mainly due to the lower participation of Hispanics vs. Non-Hispanic whites. Health insurance, having had a personal physician, having had screenings for other cancers, race, and older age are among the main predictors.^

Alpine permafrost index map

The objective of this study is the production of an Alpine Permafrost Index Map (APIM) covering the entire European Alps. A unified statistical model that is based on Alpine-wide permafrost observations is used for debris and bedrock surfaces across the entire Alps. The explanatory variables of the model are mean annual air temperatures, potential incoming solar radiation and precipitation. Offset terms were applied to make model predictions for topographic and geomorphic conditions that differ from the terrain features used for model fitting. These offsets are based on literature review and involve some degree of subjective choice during model building. The assessment of the APIM is challenging because limited independent test data are available for comparison and these observations represent point information in a spatially highly variable topography. The APIM provides an index that describes the spatial distribution of permafrost and comes together with an interpretation key that helps to assess map uncertainties and to relate map contents to their actual expression in terrain. The map can be used as a first resource to estimate permafrost conditions at any given location in the European Alps in a variety of contexts such as research and spatial planning. Results show that Switzerland likely is the country with the largest permafrost area in the Alps, followed by Italy, Austria, France and Germany. Slovenia and Liechtenstein may have marginal permafrost areas. In all countries the permafrost area is expected to be larger than the glacier-covered area.

La lógica de la inversión pública en infraestructura en la provincia de Buenos Aires : Entre las necesidades sociales y ¿la política?

El presente estudio se enfoca en la inversión en infraestructura en la provincia de Buenos Aires como un elemento central del cambio estructural pregonado para minimizar los diferenciales de productividad que constituyen la clave de los problemas del ciclo económico argentino. En el enfoque se asume la relación bidireccional entre territorio y escala nacional. Se diferencian para el análisis la infraestructura social, productiva y aquella que es consecuencia de la estructura económica dominante. Se incluye un estudio descriptivo del peso de cada tipo de infraestructura y de la lógica de localización de la inversión, y también se realiza una regresión econométrica mediante la cual se buscan variables explicativas significativas

La lógica de la inversión pública en infraestructura en la provincia de Buenos Aires : Entre las necesidades sociales y ¿la política?

El presente estudio se enfoca en la inversión en infraestructura en la provincia de Buenos Aires como un elemento central del cambio estructural pregonado para minimizar los diferenciales de productividad que constituyen la clave de los problemas del ciclo económico argentino. En el enfoque se asume la relación bidireccional entre territorio y escala nacional. Se diferencian para el análisis la infraestructura social, productiva y aquella que es consecuencia de la estructura económica dominante. Se incluye un estudio descriptivo del peso de cada tipo de infraestructura y de la lógica de localización de la inversión, y también se realiza una regresión econométrica mediante la cual se buscan variables explicativas significativas

La lógica de la inversión pública en infraestructura en la provincia de Buenos Aires : Entre las necesidades sociales y ¿la política?

El presente estudio se enfoca en la inversión en infraestructura en la provincia de Buenos Aires como un elemento central del cambio estructural pregonado para minimizar los diferenciales de productividad que constituyen la clave de los problemas del ciclo económico argentino. En el enfoque se asume la relación bidireccional entre territorio y escala nacional. Se diferencian para el análisis la infraestructura social, productiva y aquella que es consecuencia de la estructura económica dominante. Se incluye un estudio descriptivo del peso de cada tipo de infraestructura y de la lógica de localización de la inversión, y también se realiza una regresión econométrica mediante la cual se buscan variables explicativas significativas

Whale sightings, group sizes and krill biomass in West Greenland in 2005

This study combined data on fin whale Balaenoptera physalus, humpback whale Megaptera novaeangliae, minke whale B. acutorostrata, and sei whale B. borealis sightings from large-scale visual aerial and ship-based surveys (248 and 157 sightings, respectively) with synoptic acoustic sampling of krill Meganyctiphanes norvegica and Thysanoessa sp. abundance in September 2005 in West Greenland to examine the relationships between whales and their prey. Krill densities were obtained by converting relationships of volume backscattering strengths at multiple frequencies to a numerical density using an estimate of krill target strength. Krill data were vertically integrated in 25 m depth bins between 0 and 300 m to obtain water column biomass (g/m**2) and translated to density surfaces using ordinary kriging. Standard regression models (Generalized Additive Modeling, GAM, and Generalized Linear Modeling, GLM) were developed to identify important explanatory variables relating the presence, absence, and density of large whales to the physical and biological environment and different survey platforms. Large baleen whales were concentrated in 3 focal areas: (1) the northern edge of Lille Hellefiske bank between 65 and 67°N, (2) north of Paamiut at 63°N, and (3) in South Greenland between 60 and 61° N. There was a bimodal pattern of mean krill density between depths, with one peak between 50 and 75 m (mean 0.75 g/m**2, SD 2.74) and another between 225 and 275 m (mean 1.2 to 1.3 g/m**2, SD 23 to 19). Water column krill biomass was 3 times higher in South Greenland than at any other site along the coast. Total depth-integrated krill biomass was 1.3 x 10**9 (CV 0.11). Models indicated the most important parameter in predicting large baleen whale presence was integrated krill abundance, although this relationship was only significant for sightings obtained on the ship survey. This suggests that a high degree of spatio-temporal synchrony in observations is necessary for quantifying predator-prey relationships. Krill biomass was most predictive of whale presence at depths >150 m, suggesting a threshold depth below which it is energetically optimal for baleen whales to forage on krill in West Greenland.

The trade credit in the Spanish agrofood industry

Selling on credit is rather frequent in Mediterranean countries. Its generalized use can lead to excessive enlargements of the payment periods and consequently can deteriorate the profitability of firms. In spite of the relevance of this problem there are few empirical researches. This work intends to fill this gap and to shed light on the factors related to the extension of trade credit. In the theoretical and empirical literature, different motives have been proposed to explain this issue: a mechanism to reduce transaction costs, a financial alternative to the bank system and an additional tool to improve commercial activities. To contrast these ideas a panel of 388 firms of the Spanish agrofood industry has been taken, and static and dynamic regression models have been estimated by using robust methods to heteroskedasticity, autocorrelation and endogeneity of the explanatory variables. The results confirm that trade credit receivable is associated with more active firms and with cheaper bank financing. Other factors with positive relationships are short-term bank debts and accounts payable. These findings are consistent with commercial motives, rather than a pure financial view, in the sense that financial distressed producers extend trade credit as a way of promoting their products and in turn increasing their sales.

Economic analysis of drought risks: an application to irrigated agriculture in Spain

Abstract This paper describes a two-part methodology for managing the risk posed by water supply variability to irrigated agriculture. First, an econometric model is used to explain the variation in the production value of irrigated agriculture. The explanatory variables include an index of irrigation water availability (surface storage levels), a price index representative of the crops grown in each geographical unit, and a time variable. The model corrects for autocorrelation and it is applied to 16 representative Spanish provinces in terms of irrigated agriculture. In the second part, the fitted models are used for the economic evaluation of drought risk. In flow variability in the hydrological system servicing each province is used to perform ex-ante evaluations of economic output for the upcoming irrigation season. The model?s error and the probability distribution functions (PDFs) of the reservoirs? storage variations are used to generate Monte Carlo (Latin Hypercube) simulations of agricultural output 7 and 3 months prior to the irrigation season. The results of these simulations illustrate the different risk profiles of each management unit, which depend on farm productivity and on the probability distribution function of water in flow to reservoirs. The potential for ex-ante drought impact assessments is demonstrated. By complementing hydrological models, this method can assist water managers and decisionmakers in managing reservoirs.