996 resultados para bivariate probit model
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Firm-level innovation is investigated using three probit panel estimators, which control for unobserved heterogeneity, and a standard probit estimator. Results indicate the standard probit model is misspecified and that inter-firm networks are important for innovation.
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2010 Mathematics Subject Classification: 62J99.
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The main focus of this thesis was to gain a better understanding about the dynamics of risk perception and its influence on people’s evacuation behavior. Another major focus was to improve our knowledge regarding geo-spatial and temporal variations of risk perception and hurricane evacuation behavior. A longitudinal dataset of more than eight hundred households were collected following two major hurricane events, Ivan and Katrina. The longitudinal survey data was geocoded and a geo-spatial database was integrated to it. The geospatial database was composed of distance, elevation and hazard parameters with respect to the respondent’s household location. A set of Bivariate Probit (BP) model suggests that geospatial variables have had significant influences in explaining hurricane risk perception and evacuation behavior during both hurricanes. The findings also indicated that people made their evacuation decision in coherence with their risk perception. In addition, people updated their hurricane evacuation decision in a subsequent similar event.
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Using survey data for Tongan and Samoan migrants in Sydney the effects of visa restrictions on labor market performance of migrants are assessed. Univariate analysis suggests a positive association between unemployment and the unrestricted entry of Samoan step-migrants from New Zealand. A probit model of the determinants of unemployment is estimated with controls for human capital and demographic variables. While human capital endowments are important, visa restrictions do not have a significant effect on either group's employability. Implications for policy are discussed highlighting the complementarities between host country immigration policies and foreign aid programs.
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This article examines the efficiency of the National Football League (NFL) betting market. The standard ordinary least squares (OLS) regression methodology is replaced by a probit model. This circumvents potential econometric problems, and allows us to implement more sophisticated betting strategies where bets are placed only when there is a relatively high probability of success. In-sample tests indicate that probit-based betting strategies generate statistically significant profits. Whereas the profitability of a number of these betting strategies is confirmed by out-of-sample testing, there is some inconsistency among the remaining out-of-sample predictions. Our results also suggest that widely documented inefficiencies in this market tend to dissipate over time.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics
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This paper intends to study whether financial liberalization tends to increase the likelihood of systemic banking crises. I used a sample of 79 countries with data spanning from 1973 to 2005 to run a panel probit model. I found that, if anything, financial liberalization as measured across seven different dimensions tends to decrease the probability of occurrence of a systemic banking crisis. I went further and did several robustness tests – used a conditional probit model, tested for different durations of liberalization impact and reduced the sample by considering only the first crisis event for each country. Main results still verified, proving the results’ robustness.
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We study the determinants of MRI use across Portuguese NHS hospitals for patients belonging to specific DRGs. Using data on individual hospital admissions, we estimate a probit model including individual-, hospital-, time- and region-specific variables in order to explain the probability of a patient being sent for MRI. Results convey a tightening effect on the hospital’s budget constraint in the end of each year. Hospitals seem to account for regional characteristics when defining adoption patterns. Individual-specific variables are good predictors of MRI use. Measures taken by the Government only impact the short run. Finally, the gains from an MRI scan, as far as the probability of death is concerned, occur mainly for less severe patients.
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The present paper aims to investigate the determinant factors of Portuguese merger control. Our sample comprises 652 M&A cases occurred between January of 2003 and September of 2015. Through a probit model we have tested the relevance of product and geographic market, entry barriers, type of concentration, merger effects, year of decision and the President of the Competition Authority at the time. The results suggests that the conglomerate and vertical effects, the existence of barriers to entry as well as the number of regulatory agencies listened are the main explanatory variables to determine a need for an in-depth investigation and to make a final decision. According to the evidence, cases cleared at Phase 1 are increasing over time. The number of prohibited mergers is close to zero.
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During the last two decades there has been an increase in using dynamic tariffs for billing household electricity consumption. This has questioned the suitability of traditional pricing schemes, such as two-part tariffs, since they contribute to create marked peak and offpeak demands. The aim of this paper is to assess if two-part tariffs are an efficient pricing scheme using Spanish household electricity microdata. An ordered probit model with instrumental variables on the determinants of power level choice and non-paramentric spline regressions on the electricity price distribution will allow us to distinguish between the tariff structure choice and the simultaneous demand decisions. We conclude that electricity consumption and dwellings’ and individuals’ characteristics are key determinants of the fixed charge paid by Spanish households Finally, the results point to the inefficiency of the two-part tariff as those consumers who consume more electricity pay a lower price than the others.
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The contributions of this paper are twofold: On the one hand, the paper analyses the factors determining the growth in car ownership in Spain over the last two decades, and, on the other, the paper provides empirical evidence for a controversial methodological issue. From a methodological point of view, the paper compares the two alternative decision mechanisms used for modelling car ownership: ordered-response versus unordered-response mechanisms. A discrete choice model is estimated at three points in time: 1980, 1990 and 2000. The study concludes that on the basis of forecasting performance, the multinomial logit model and the ordered probit model are almost undistinguishable. As for the empirical results, it can be emphasised that income elasticity is not constant and declines as car ownership increases. Besides, households living in rural areas are less sensitive than those living in urban areas. Car ownership is also sensitive to the quality of public transport for those living in the largest cities. The results also confirmed the existence of a generation effect, which will vanish around the year 2020, a weak life-cycle effect, and a positive effect of employment on the number of cars per household. Finally, the change in the estimated coefficients over time reflects an increase in mobility needs and, consequently, an increase in car ownership.
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This paper is inspired by articles in the last decade or so that have argued for more attention to theory, and to empirical analysis, within the well-known, and long-lasting, contingency framework for explaining the organisational form of the firm. Its contribution is to extend contingency analysis in three ways: (a) by empirically testing it, using explicit econometric modelling (rather than case study evidence) involving estimation by ordered probit analysis; (b) by extending its scope from large firms to SMEs; (c) by extending its applications from Western economic contexts, to an emerging economy context, using field work evidence from China. It calibrates organizational form in a new way, as an ordinal dependent variable, and also utilises new measures of familiar contingency factors from the literature (i.e. Environment, Strategy, Size and Technology) as the independent variables. An ordered probit model of contingency was constructed, and estimated by maximum likelihood, using a cross section of 83 private Chinese firms. The probit was found to be a good fit to the data, and displayed significant coefficients with plausible interpretations for key variables under all the four categories of contingency analysis, namely Environment, Strategy, Size and Technology. Thus we have generalised the contingency model, in terms of specification, interpretation and applications area.