Bank systemic risk: An analysis of the sovereign rating ceiling policy and rating downgrades

We investigate the impact that the sovereign ceiling policy has on financial stability. In the event of a sovereign rating downgrade, we find that the rating agencies' sovereign ceiling policy leads to a disproportionate downgrade of the most creditworthy financial institutions in the economy and results in increased systemic risk. This asymmetric variation in bank ratings also impairs equity growth that further exacerbates bank insolvency. Our results are robust to several matching techniques, such as propensity score matching and entropy balancing, falsification tests, subsample analyses, alternative empirical proxies and model specifications.     

Licensing cost-reducing innovations under supply function competition

In this paper, we study the licensing of cost-reducing innovations in a duopoly under supply function competition. We show that the innovator prefers fixed-fee licensing to no licensing if its cost advantage is not extremely large. Moreover, if its cost advantage is not extremely small, the innovator prefers fixed-fee licensing and mixed licensing to revenue-royalty licensing. This second result arises only because of our assumption that the cost functions are quadratic. We show that if the cost functions are linear and royalty payments are per unit of output, the innovator strictly prefers royalty licensing to fixed-fee licensing. We also show that in our model, consumer surplus is remarkably higher under any type of licensing than under no licensing. However, revenue-royalty licensing is slightly superior for consumers to the other two types of licensing and only so if the cost advantage of the innovator is sufficiently large.     

Cultural influences on future transportation technology usage: The role of personal innovativeness,technology anxiety and desire

This study develops and validates a model, based on personal cultural values theory and psychological research, in relation to technology adoption. The model focuses specifically on the future use of on-demand air mobility (ODAM), which is expected to have significant implications for city commuting and personal well-being in the years ahead. We use a path modelling approach, in addition to recently advanced analytical methods such as the finite mixture partial least squares (FIMIX-PLS), measurement invariance of composite models (MICOM) and multi-group analysis, to validate the model using a data set of 627 young consumers from the Czech Republic. The research model explains 45.2% variation in the future use of ODAM using our global model. This variance explained in the future use of ODAM increases to 62.3% and 64.5% respectively, when we segment our data set into two groups. The results also show that tradition has significant influence on technology anxiety, personal innovativeness and desire to use ODAM. Independence positively affects personal innovativeness but not the desire to use ODAM. We also find that technology anxiety influences the desire to use, which in turn influences the future use of ODAM. However, we find group differences in the influence of ambiguity intolerance on technology anxiety, desire and personal innovativeness. Thus, the study also evaluates the existence of significant differences between two groups in our data set. Overall, the study suggests that individual cultural values play a particularly important role in influencing the future use of ODAM through psychological characteristics. The research implications of the study are discussed in the article.     

The role of social networks in the adoption of competing new technologies in Ghana

We use a detailed dataset to examine the impact of social networks, conditional on contextual and individual confounders, on farmers' adoption of competing improved soybean varieties in Ghana. Based on the contagion conceptual framework, we employ a spatial autoregressive multinomial probit model to examine how neighbours' varietal and cross-varietal adoption of improved varieties affect a farmer's adoption decision in the social network. Our results show that adoption decisions in a network tend to converge on one variety, such that beyond a threshold of adopting neighbours of that improved variety, the cross-varietal effects tend to lose significance in the network. If the shares of adopting neighbours of the improved varieties are equal, we find evidence that farmers are not more likely to adopt either improved variety compared to farmers with no neighbours who have adopted the improved varieties. The findings demonstrate the significance of neighbourhood effects in the adoption of competing technologies.     

The political economy triangle of government spending,interest-group influence,and income inequality: Evidence and implications from the US states

This paper introduces the political economy triangle (PET) concept of government spending, special interest groups (SIGs) influence, and income inequality, empirically confirming its existence and unveiling its nature while directly addressing key shortcomings of most prior research on the determinants of such inequality. Using static and dynamic panel techniques and data from the US states, it reports several new results: (i) the findings of previous studies regarding the roles of government spending and interest groups, including labor unions, in income distribution are confirmed, however, their estimated inequality effects grossly underestimate those obtained when endogeneity issues are accounted for explicitly; (ii) a dynamic tripartite relationship between the variables of the PET exists; (iii) government spending and SIGs' influence, including union strength, beyond their direct effects on inequality, have a separate positive impact through their interactions; (iv) the effectiveness of government spending in reducing inequality diminishes as the level of SIGs' influence and union strength increase in the short and long run, (v) the aggregate inequality-increasing effect of SIGs is strengthened and the inequality-reducing effects of unions weakened as the spending rises, in the short run and long run. Finally, the broad implications of these findings are discussed.     

Utilising farm-level panel data to estimate climate change impacts and adaptation potentials

We combine farm accounting data with high-resolution meteorological data, and climate scenarios to estimate climate change impacts and adaptation potentials at the farm level. To do so, we adapt the seminal model of Moore and Lobell (2014) who applied panel data econometrics to data aggregated from the farm to the regional (subnational) level. We discuss and empirically investigate the advantages and challenges of applying such models to farm-level data, including issues of endogeneity of explanatory variables, heterogeneity of farm responses to weather shocks, measurement errors in meteorological variables, and aggregation bias. Empirical investigations into these issues reveal that endogeneity due to measurement errors in temperature and precipitation variables, as well as heterogeneous responses of farms toward climate change may be problematic. Moreover, depending on how data are aggregated, results differ substantially compared to farm-level analysis. Based on data from Austria and two climate scenarios (Effective Measures and High Emission) for 2040, we estimate that the profits of farms will decline, on average, by 4.4% (Effective Measures) and 10% (High Emission). Adaptation options help to considerably ameliorate the adverse situation under both scenarios. Our results reinforce the need for mitigation and adaptation to climate change.