Gender-preferential intergenerational patterns in primary education attainment : a quantitative analysis of a case of rural Mindanao, the Philippines

The Philippines has achieved a relatively high standard of education. Previous researches, most of which deal with Luzon Island, have indicated that rural poverty alleviation began partly due to the increased investment in education. However, the suburban areas beyond Luzon Island have rarely been studied. This study examines a case from rural Mindanao, and investigates the determinants and factors associated with children's education, with a special focus on delays in schooling, which may be a cause of dropout and holdover incidences, as well as exploring gender-specific differential patterns. The result shows that after controlling other socioeconomic attributes, (1) delays in schooling, as well as years completed, are more favorable for girls than boys; (2) the level of maternal education is equally associated with the child(ren)’s education level regardless of their gender; and (3) paternal education is preferentially and favorably influential to the same-gender child(ren), i.e., son(s). To reduce the boy-unfriendly gender bias in primary education, this study suggests two future tasks, i.e., providing boy-specific interventions to enhance the magnitude of the father-son educational virtuous circle, and comparing the magnitude of gender-equal maternal education influence and boy-preferential paternal education influence to specify which effect is larger.

Identification of MIMO Hammerstein systems using cardinal spline functions

A new approach to identify multivariable Hammerstein systems is proposed in this paper. By using cardinal cubic spline functions to model the static nonlinearities, the proposed method is effective in modelling processes with hard and/or coupled nonlinearities. With an appropriate transformation, the nonlinear models are parameterized such that the nonlinear identification problem is converted into a linear one. The persistently exciting condition for the transformed input is derived to ensure the estimates are consistent with the true system. A simulation study is performed to demonstrate the effectiveness of the proposed method compared with the existing approaches based on polynomials. (C) 2006 Elsevier Ltd. All rights reserved.

Comparing methods to separate treatment from self-selection effects in an online banking setting

The literature discusses several methods to control for self-selection effects but provides little guidance on which method to use in a setting with a limited number of variables. The authors theoretically compare and empirically assess the performance of different matching methods and instrumental variable and control function methods in this type of setting by investigating the effect of online banking on product usage. Hybrid matching in combination with the Gaussian kernel algorithm outperforms the other methods with respect to predictive validity. The empirical finding of large self-selection effects indicates the importance of controlling for these effects when assessing the effectiveness of marketing activities.

Externalities of openness in innovation

Discussion of open innovation has typically stressed the benefits to the individual enterprise from boundary-spanning linkages and improved internal knowledge sharing. In this paper we explore the potential for wider benefits from openness in innovation and argue that openness may itself generate positive externalities by enabling improved knowledge diffusion. The potential for these (positive) externalities suggests a divergence between the private and social returns to openness and the potential for a sub-optimal level of openness where this is determined purely by firms' private returns. Our analysis is based on Irish plant-level panel data from manufacturing industry over the period 1994-2008. Based on instrumental variables regression models our results suggest that externalities of openness in innovation are significant and that they are positively associated with firms' innovation performance. We find that these externality effects are unlikely to work through their effect on the spread of open innovation practices. Instead, they appear to positively influence innovation outputs by either increasing knowledge diffusion or strengthening competition. Our evidence on the significance of externalities from openness in innovation provides a rationale for public policy aimed at promoting open innovation practices among firms. © 2013 Elsevier B.V. All rights reserved.

The impact of university research on corporate patenting

This paper analyses the association between the number of patenting manufacturing firms and the quantity and quality of relevant university research across UK postcode areas. We show that different measures of research `power' and `excellence' positively affect the patenting of small firms within the same postcode area. Patenting by large firms, in contrast, is unaffected by research undertaken in nearby universities. This confirms the commonly held view that location matters more for small firms than large firms. We also investigate specific channels of technology transfer, finding that university-industry knowledge transfer occurs through both formal and informal channels. From a methodological point of view, we contribute to the existing literature by accounting for potential simultaneity between university research and patenting of local firms by adopting an instrumental variable approach. Moreover, we also allow for the effects of the presence of universities in neighbouring postcode areas to influence firms' patenting activity by incorporating spatial neighborhood effects.

Essays on Microeconometrics

My dissertation has three chapters which develop and apply microeconometric tech- niques to empirically relevant problems. All the chapters examines the robustness issues (e.g., measurement error and model misspecification) in the econometric anal- ysis. The first chapter studies the identifying power of an instrumental variable in the nonparametric heterogeneous treatment effect framework when a binary treat- ment variable is mismeasured and endogenous. I characterize the sharp identified set for the local average treatment effect under the following two assumptions: (1) the exclusion restriction of an instrument and (2) deterministic monotonicity of the true treatment variable in the instrument. The identification strategy allows for general measurement error. Notably, (i) the measurement error is nonclassical, (ii) it can be endogenous, and (iii) no assumptions are imposed on the marginal distribution of the measurement error, so that I do not need to assume the accuracy of the measure- ment. Based on the partial identification result, I provide a consistent confidence interval for the local average treatment effect with uniformly valid size control. I also show that the identification strategy can incorporate repeated measurements to narrow the identified set, even if the repeated measurements themselves are endoge- nous. Using the the National Longitudinal Study of the High School Class of 1972, I demonstrate that my new methodology can produce nontrivial bounds for the return to college attendance when attendance is mismeasured and endogenous.

The second chapter, which is a part of a coauthored project with Federico Bugni, considers the problem of inference in dynamic discrete choice problems when the structural model is locally misspecified. We consider two popular classes of estimators for dynamic discrete choice models: K-step maximum likelihood estimators (K-ML) and K-step minimum distance estimators (K-MD), where K denotes the number of policy iterations employed in the estimation problem. These estimator classes include popular estimators such as Rust (1987)’s nested fixed point estimator, Hotz and Miller (1993)’s conditional choice probability estimator, Aguirregabiria and Mira (2002)’s nested algorithm estimator, and Pesendorfer and Schmidt-Dengler (2008)’s least squares estimator. We derive and compare the asymptotic distributions of K- ML and K-MD estimators when the model is arbitrarily locally misspecified and we obtain three main results. In the absence of misspecification, Aguirregabiria and Mira (2002) show that all K-ML estimators are asymptotically equivalent regardless of the choice of K. Our first result shows that this finding extends to a locally misspecified model, regardless of the degree of local misspecification. As a second result, we show that an analogous result holds for all K-MD estimators, i.e., all K- MD estimator are asymptotically equivalent regardless of the choice of K. Our third and final result is to compare K-MD and K-ML estimators in terms of asymptotic mean squared error. Under local misspecification, the optimally weighted K-MD estimator depends on the unknown asymptotic bias and is no longer feasible. In turn, feasible K-MD estimators could have an asymptotic mean squared error that is higher or lower than that of the K-ML estimators. To demonstrate the relevance of our asymptotic analysis, we illustrate our findings using in a simulation exercise based on a misspecified version of Rust (1987) bus engine problem.

The last chapter investigates the causal effect of the Omnibus Budget Reconcil- iation Act of 1993, which caused the biggest change to the EITC in its history, on unemployment and labor force participation among single mothers. Unemployment and labor force participation are difficult to define for a few reasons, for example, be- cause of marginally attached workers. Instead of searching for the unique definition for each of these two concepts, this chapter bounds unemployment and labor force participation by observable variables and, as a result, considers various competing definitions of these two concepts simultaneously. This bounding strategy leads to partial identification of the treatment effect. The inference results depend on the construction of the bounds, but they imply positive effect on labor force participa- tion and negligible effect on unemployment. The results imply that the difference- in-difference result based on the BLS definition of unemployment can be misleading

due to misclassification of unemployment.

Cross-section and panel estimates of peer effects in early adolescent cannabis use: With a little help from my ‘friends once removed’

Peer effects in adolescent cannabis are difficult to estimate, due in part to the lack of appropriate data on behaviour and social ties. This paper exploits survey data that have many desirable properties and have not previously been used for this purpose. The data set, collected from teenagers in three annual waves from 2002-2004 contains longitudinal information about friendship networks within schools (N = 5,020). We exploit these data on network structure to estimate peer effects on adolescents from their nominated friends within school using two alternative approaches to identification. First, we present a cross-sectional instrumental variable (IV) estimate of peer effects that exploits network structure at the second degree, i.e. using information on friends of friends who are not themselves ego’s friends to instrument for the cannabis use of friends. Second, we present an individual fixed effects estimate of peer effects using the full longitudinal structure of the data. Both innovations allow a greater degree of control for correlated effects than is commonly the case in the substance-use peer effects literature, improving our chances of obtaining estimates of peer effects than can be plausibly interpreted as causal. Both estimates suggest positive peer effects of non-trivial magnitude, although the IV estimate is imprecise. Furthermore, when we specify identical models with behaviour and characteristics of randomly selected school peers in place of friends’, we find effectively zero effect from these ‘placebo’ peers, lending credence to our main estimates. We conclude that cross-sectional data can be used to estimate plausible positive peer effects on cannabis use where network structure information is available and appropriately exploited.

Finite Population Inference for Causal Parameters

Thesis (Ph.D.)--University of Washington, 2016-08

Testing mediation: The endogeneity problem and the solution

A mediator is a dependent variable, m (e.g., charisma), that is thought to channel the effect of an independent variable, x (e.g., receiving training or not), on another dependent variable (e.g., subordinate satisfaction), y. In experimental settings x is manipulated-subjects are randomized to treatment-to isolate the causal effect of x on other variables. If m is not or cannot be manipulated, which is often the case, its causal effect on other variables cannot be determined; thus, standard mediation tests cannot inform policy or practice. I will show how an econometric procedure, called instrumental-variable estimation, can examine mediation in such cases.

Determinants of non-life insurance expenditure in developed and developing countries: an empirical investigation

The determinants of non-life insurance expenditure in a panel data set covering 36 developed countries and 31 developing countries for the period 2000–2011 are analysed. Results of our instrumental variable analysis indicate that economic freedom, income, bank development, urbanization, culture and law systems are the key drivers of the non-life insurance expenditure across countries. However, their impacts differ significantly between the groups of developed and developing countries, suggesting that the heterogeneity among countries in terms of the level of development plays an important role. The global financial crisis is also found to influence the direction of those effects, especially in developed countries. The article yields useful policy and economic implications for governments and multinational non-life insurance companies with regard to the development of the non-life insurance sector, an important engine for economic growth and prosperity.

Bureaucratic corruption and income : evidence from the land sector in Bangladesh

We examine, for the first time, the effects of corruption on income using household survey data from a developing country. Estimating the effects of corruption on income is challenging because of the simultaneous relationship between the two variables. We use a two-step instrumental variable approach to identify the effects of corruption on income. We find that after adjusting for simultaneity bias the act of bribery reduces income and that higher bribes have a negative effect on income. Taken together, our results provide a possible explanation why a vicious cycle between corruption and income inequality does not exist in the land sector in Bangladesh.

The role of cultural heritage in attracting skilled individuals

The purpose of this paper is to examine the role played by built heritages and cultural environments, alongside other locational factors, in explaining the growth of human capital in Sweden. We distinguish between urban, natural and cultural qualities as different sources of regional attractiveness and estimate their influence on the observed growth of individuals with at least three years of higher education during 2001–2010. Neighborhood-level data are used, and unobserved heterogeneity and spatial dependencies are modeled by employing random effects estimations and an instrumental variable approach. Our findings indicate that the local supply of built heritages and cultural environments explain a significant part of human capital growth in Sweden. Results suggest that these types of cultural heritages are important place-based resources with a potential to contribute to improved regional attractiveness and growth.

Cystatin C and cardiovascular disease : A mendelian randomization study

BACKGROUND: Epidemiological studies show that high circulating cystatin C is associated with risk of cardiovascular disease (CVD), independent of creatinine-based renal function measurements. It is unclear whether this relationship is causal, arises from residual confounding, and/or is a consequence of reverse causation. OBJECTIVES: The aim of this study was to use Mendelian randomization to investigate whether cystatin C is causally related to CVD in the general population. METHODS We incorporated participant data from 16 prospective cohorts (n ¼ 76,481) with 37,126 measures of cystatin C and added genetic data from 43 studies (n ¼ 252,216) with 63,292 CVD events. We used the common variant rs911119 in CST3 as an instrumental variable to investigate the causal role of cystatin C in CVD, including coronary heart disease, ischemic stroke, and heart failure. RESULTS: Cystatin C concentrations were associated with CVD risk after adjusting for age, sex, and traditional risk factors (relative risk: 1.82 per doubling of cystatin C; 95% confidence interval [CI]: 1.56 to 2.13; p ¼ 2.12 1014). The minor allele of rs911119 was associated with decreased serum cystatin C (6.13% per allele; 95% CI: 5.75 to 6.50; p ¼ 5.95 10211), explaining 2.8% of the observed variation in cystatin C. Mendelian randomization analysis did not provide evidence for a causal role of cystatin C, with a causal relative risk for CVD of 1.00 per doubling cystatin C (95% CI: 0.82 to 1.22; p ¼ 0.994), which was statistically different from the observational estimate (p ¼ 1.6 105 ). A causal effect of cystatin C was not detected for any individual component of CVD. CONCLUSIONS: Mendelian randomization analyses did not support a causal role of cystatin C in the etiology of CVD. As such, therapeutics targeted at lowering circulating cystatin C are unlikely to be effective in preventing CVD. 

The regional impact of cultural diversity on wages: evidence from Australia

This paper investigates the impact of cultural diversity on labour market outcomes, particularly on wages across regions using a large longitudinal data. We apply an instrumental variable approach and account for individual and time fixed effects. Our findings indicate that the current level of cultural diversity positively affected current regional weekly wages; however, the positive effect holds only partially when the diversity is lagged. The results appear to be robust in all estimations controlling for heterogeneity factors and accounting for the self-selection of individuals into places with better economic opportunities. Our findings concerning the effect of lagging on the effect of diversity may explain the variation in the literature where some studies report that cultural diversity increases wages across time while others do not.

BM: Tributación y concentración en el sistema financiero Colombiano 1989 - 2003

El presente documento analiza los determinantes del margen de intermediación para el sistema financiero colombiano entre 1989 y 2003. Bajo una estimación dinámica de los efectos generados por variables específicas de actividad, impuestos y estructura de mercado, se presenta un seguimiento del margen de intermediación financiero, para un período que presenta elementos de liberalización y crisis.