Exploring injury severity of pedestrian-vehicle crashes at intersections: unbalanced panel mixed ordered probit model

Although the pedestrian deaths have been declining in recent years, the pedestrian-vehicle death rate in Croatia is still pretty high. This study intended to explore the injury severity of pedestrian-vehicle crashes with panel mixed ordered probit model and identify the influencing factors at intersections. To achieve this objective, the data were collected from Ministry of the Interior, Republic of Croatia from 2015 to 2018. Compared to the equivalent random-effects and random parameter ordered probit models, the proposed model showed better performance on goodness-of-fit, while capturing the impact of exogenous variables to vary among the intersections, as well as accommodating the heterogeneity issue due to unobserved effects. Results revealed that the proposed model can be considered as an alternative to deal with the heterogeneity issue and to decide the factor determinants. The results may provide beneficial insight for reducing the injury severity of pedestrian-vehicle crashes.

Effects of Sales Tax Competition on Local Revenue Capacity: Empirical Analysis of California County Governments

This study empirically examines the effects of tax competition in both horizontal and vertical ways on the revenue capacity of counties in California from 2003 to 2015. Spatial Durbin model (SDM) identifies the effects of two-way tax competition on a county’s revenue capacity. The findings provide evidence that local sales tax helps a county expand its total revenue, but the two-way tax competition brings about a decrease in local revenue capacity as a result of spillovers. Furthermore, a lower-taxing area can have more benefits because the expansions in the neighbors are much greater than the higher-taxing one. In spite of the extant research of tax competition, this study adds another contribution to this research arena that the empirical approach of the SDM rules out the geospatial effects of the other explanatory variables that might have some unobserved effects in the extant literature.

Does official development assistance affect a donor’s exports? South Korea’s case

This paper studies the impact of official development assistance (ODA) provided by South Korea for its exports to recipient countries. The empirical analysis is based on data from 1996 to 2014 and covers 121 recipient countries. The paper uses a 3SLS estimation method that accounts for a two-way causal relationship between ODA and exports while the endogeneity and sample selection bias are accounted for. Using the gravity model, we confirm the positive effects of ODA when fixed unobserved effects are controlled. The model is further generalized by disaggregating ODA into its underlying types of aid. Our results show that technical cooperation and loans have positive and significant effects, but grants have a negative impact on South Korea’s exports to recipient countries. In addition, we also examine South Korea’s ODA allocations. Our findings suggest that there is a two-stage decision-making process in the provision of aid. In the first stage, the aid’s humanitarian purpose plays a key role in responding to countries’ needs even when there is lower bilateral trade with these countries. In the second stage, decisions regarding the size of ODA are considered and these present a mixed purpose for giving ODA to higher importer countries.

Does rehabilitation setting influence risk of institutionalization? A register-based study of hip fracture patients in Oslo, Norway

Background Reducing the economic impact of hip fractures (HF) is a global issue. Some efforts aimed at curtailing costs associated with HF include rehabilitating patients within primary care. Little, however, is known about how different rehabilitation settings within primary care influence patients’ subsequent risk of institutionalization for long-term care (LTC). This study examines the association between rehabilitation setting (outside an institution versus short-term rehabilitation stay in an institution, both during 30 days post-discharge for HF) and risk of institutionalization in a nursing home (at 6–12 months from the index admission). Methods Data were for 612 HF incidents across 611 patients aged 50 years and older, who were hospitalized between 2008 and 2013 in Oslo, Norway, and who lived at home prior to the incidence. We used logistic regression to examine the effect of rehabilitation setting on risk of institutionalization, and adjusted for patients’ age, gender, health characteristics, functional level, use of healthcare services, and socioeconomic characteristics. The models also included fixed-effects for Oslo’s boroughs to control for supply-side and unobserved effects. Results The sample of HF patients had a mean age of 82.4 years, and 78.9 % were women. Within 30 days after hospital discharge, 49.0 % of patients received rehabilitation outside an institution, while the remaining 51.0 % received a short-term rehabilitation stay in an institution. Receiving rehabilitation outside an institution was associated with a 58 % lower odds (OR = 0.42, 95 % CI = 0.23–0.76) of living in a nursing home at 6–12 months after the index admission. The patients who were admitted to a nursing home for LTC were older, more dependent on help with their memory, and had a substantially greater increase in the use of municipal healthcare services after the HF. Conclusions The setting in which HF patients receive rehabilitation is associated with their likelihood of institutionalization. In the current study, patients who received rehabilitation outside of an institution were less likely to be admitted to a nursing home for LTC, compared to those who received a short-term rehabilitation stay in an institution. These results suggest that providing rehabilitation at home may be favorable in terms of reducing risk of institutionalization for HF patients.

Modeling Spatial Interaction in Stochastic Frontier Analysis

We compare farm level efficiency rankings derived from non-spatial and a variety of spatial model specifications that account for unobserved heterogeneity in both the production and the efficiency sides of the stochastic frontier model in an empirical application on rice farming in the Philippines. We show how not accounting for unobserved spatial heterogeneity affects efficiency estimates and farm efficiency rankings. When not accounting for unobserved spatial heterogeneity efficiency, models show farms to be relatively more inefficient than they actually are (i.e., once unobserved spatial heterogeneity is incorporated in the models). More importantly from a policy perspective, the rankings of the farms in terms of efficiency are altered once unobserved spatial heterogeneity is incorporated in efficiency models. We recommend the use of unobserved effects in both production and efficiency within the stochastic frontier analysis framework to avoid making any misleading recommendations to farmers and policymakers.

The effects of health shocks on family status: do financial incentives encourage marriage?

This paper asks whether marriage decisions of unmarried mature couples are driven by the prospect of financial advantages for the later widowed after one partner has suffered a serious health shock. We hypothesize that, in contrast to traditional marriage models, such health shocks may induce unmarried couples to obtain economic benefits, such as survivors’ pensions in particular, through marriage in advance of one partner’s death. This question has not yet been studied empirically. Hazard models capturing unobserved effects are applied to longitudinal data of the German Socioeconomic Panel. It turns out that the probability of marriage after male partners’ health shocks can increase significantly depending on the amount of expected survivors’ pensions for the (likely) surviving female partners. In contrast, an increased probability of marriage after health shocks to women (depending on the expected financial benefits to men) was not found. These findings are supported by various robustness checks. Economic and political implications are discussed and the results are placed in an international context.

Pharmaceutical Product Liability, Litigation Regimes, and the Propensity to Patent: An Empirical Firm-Level Investigation

Do different pharmaceutical product liability regimes in different countries induce propensity to patent? We exploit the variation in pharmaceutical liability and litigation rules across firms in the pharmaceutical industry and countries to explain the firm-level propensity to patent. Drawing on a large dataset from European Patent Office (EPO) covering over 9,950 pharmaceutical patents from 63 countries over the period 1991–2015, we compute the conditional probabilities of individual pharmaceutical firms to acquire a valid-based patent on the validation outcomes and examine whether different liability regimes encourage or deter firm-level propensity to patent. Our empirical strategy addresses firm-level idiosyncrasies, country-level unobserved effects, and common technology shocks that potentially invoke omitted variable bias in the effects of liability regimes on the propensity to patent. Our investigation reveals that liability regimes combined with damage caps, broad statutory excuses, and reversed burden of proof have a strong positive effect on the firm-level patent stock and a negative effect upon EPO patent validation rate. The evidence suggests that not all liability rules and related litigation procedures are created equal. Firms are systematically more likely to hold (firm-level patent stock) valid patents at the EPO when the liability and litigation rules are not complex and when the damage cap, broad statutory excuses, and reversed burden of proof are introduced.

Exploring the relationship between Airbnb and traditional accommodation for regional variations of tourism markets

The relationship between Airbnb-based and traditional accommodation is mainly documented for key tourist destinations with a large tourism sector, while there is almost no evidence on this for other destinations. This article focuses on regional variations in the relationship between Airbnb-based and traditional accommodation across primary and secondary tourist destinations in Norway. Through an exploratory cluster analysis and a panel vector autoregressive (PVAR) model with forecast error decomposition of shocks (unobserved effects), it finds evidence of spillovers from Airbnb-based accommodation to traditional accommodation in secondary destinations. The demand for traditional accommodation is positively affected by Airbnb demand in the long run. Interestingly, a smaller effect is found with the supply-side of regional tourism markets in the Norwegian secondary tourist destinations. The growth of Airbnb may, thus, spur growth in the general tourism sector in such less frequented destinations.

Solving the Muni Puzzle: Who Benefits from Tax Exemption of Government Debt?

I provide a new approach to measuring interest savings associated with issuing tax-exempt municipal bonds (munis) and present empirical evidence offering a solution to the long-standing “muni puzzle.” I show that the tax policy is effective and consistent with theory once I account for idiosyncratic issuer risk and investor preferences. I match tax-exempt munis to near-identical taxable munis issued by the same government at the same time with the same security characteristics to identify the slope of and the trend in implied marginal tax rates. Results of the random coefficients model, which mitigates issuer- and issuance-level unobserved effects, predict the slope of the marginal tax rate to be consistent with asset pricing theory and the tax profile of the typical muni investor. Findings also imply cyclicality over time and heterogeneity in implied marginal tax rates across issuers due to variations in idiosyncratic risk.