Applied Economics

If fan demand is driven by balanced competition and/or the spectacle of the game, then all teams can do well. However, if winning is what really counts, life becomes very difficult for the teams at the bottom of the standings each year. In contrast to the dominant role played by television and media rights today, the calculation was more clear-cut during US baseball's early days when simply getting fans in the stands was what paid the bills. Although our panel data analysis shows that other factors like home runs hit and competitive balance were also significant over the 1892-1940 period, it appears that fans then, like today, mostly just wanted to see their favorite team win. * The authors are grateful to two anonymous referees for helpful comments.

The COVID-19 pandemic has severely affected the tourism sector and the survival of hospitality firms. This study examines how hospitality firms' financial characteristics prior to the outbreak of the pandemic determined their financial resilience. We analysed a sample of large European firms operating in the hospitality industry from 2016 to 2020. Using ordinary least squares, we find significant impacts of both COVID-19 incidence (negative) and the strength of the health system (positive) on firms' financial health. Our results show that firms' recent pre-COVID-19 profitability, leverage, tangibility, and liquidity histories are key drivers of their financial health in the presence of this exogenous and extremely negative shock. Furthermore, a contextual macroeconomic factor, the interest rate, introduced as a proxy for external financial restrictions, plays a key role in the effects of liquidity and debt on firms' financial health. With higher interest rates, firms accumulated liquidity during the years prior to the pandemic, making them more resilient to the shock; in contrast, with lower interest rates, a history of limited leverage and tangibility contributed to making hospitality firms more resilient in 2020.

We investigate the performance of pairs trading strategies based on Ornstein-Uhlenbeck (OU) process with jump-diffusion and regime-switching using minute-level data for five Chinese energy futures from 2 January 2020 to 30 November 2021 and compare them with traditional pairs trading strategies. Our results indicate that OU models can obtain an average return of 50.62% per annum and a Sharpe ratio of 2.63, which significantly exceed those of traditional pairs trading strategies. However, none of them could ‘win’ in every subperiod with diverse market conditions. Meanwhile, we find that introducing jump-diffusion indeed improves the performance (additional 25.37% annualized return and 1.12 Sharpe ratio). In contrast, considering more regimes does not always bring additional benefits. Robustness checks show that the superior performance of three-regime switching OU model (3RS-OUM) persists even under harsh trading conditions.

Environmental justice is an important part of the environmental governance system. We use the exogenous shock of the environmental public interest litigation (EPIL) pilot implemented by the Chinese government in 2015 to construct a quasi-natural experiment and employ the difference-indifferences (DID) model to examine the impact and its mechanisms of environmental judicial protection on urban green technology innovation (GTI) with the help of the panel data of 274 cities in China from 2011 to 2019. The results show that the EPIL policy can significantly promote urban GTI. Mechanism tests reveal that the EPIL policy can induce urban GTI by raising public environmental attention (PEA) and strengthening the application of digital technology (DE). Heterogeneous analyses indicate that the promoting effect is more significant in eastern cities, southern cities, cities with higher administrative levels, larger cities, and cities with higher economic development levels. Our study not only enriches the relevant literature in the field of 'law and economics', but also provides a reference for policymakers to scientifically implement EPIL policy.

In this study, Okun’s law is empirically assessed for the 257 NUTS2 (Nomenclature of Territorial Units for Statistics) European regions over the period 2010–2020, which is characterised by intense economic, societal and political changes as a consequence of the 2009 economic crisis, the austerity measures followed and the COVID-19 pandemic outbreak. Okun’s law equation is estimated using instrumental variables regression, employing a two-step methodology: (1) a panel regression estimator to obtain predicted variables of the endogenous variable (Gross Domestic Product (GDP) % change) by including the appropriate instruments in the model, (2) a linear-mixed fixed, random coefficient model and empirical Bayes predictions for the random intercepts and random slopes to obtain Okun’s coefficients. Study results confirm the Okun’s law for all regions under consideration and suggest that unemployment responses to economic growth differ among regions; either due to business cycle effects or structural labour-market factors. For regions depicting the strongest inverse impact of GDP on unemployment, a cyclical recovery is expected to be accompanied by a reduction in unemployment; while the weakest inverse relationship observed is associated with structural factors (i.e. industry composition, labour-force skills, long-term unemployment). At policymaking level, considering regional labour-market idiosyncrasies is of utmost importance to differentiate labour policies.

In most developed countries, patients have been encouraged to elect their preferred choice of health care provider. However, this is different for specialized care, where the patient’s referral could be defined as a two-stage decision process and their options are pre-selected by their general practitioner (GP). In this study, we estimate patient preferences while controlling for the pre-selection procedure, and we investigate whether patients are actively choosing their provider for cancer care. The French national hospital discharge database (Programme de Médicalisation des Systèmes d’Information, PMSI – MCO 2017) has been used for investigation. We estimated a multinomial choice model when choice sets are in fact unobserved, which is assumed to identify patient preferences, in a revealed preferences framework. Our findings provide evidence that patients consider factors other than distance to select their provider. The patient – hospital distance as well as the specialization profile of providers appears to be internalized in the pre-selection process, while patients rather consider waiting times, hospital quality, and other provider attributes to make their final choice. We also found that patients would be treated in higher-quality hospitals if they had the opportunity to choose among all available providers.