Spatial econometric models allow for interactions among cross-sectional units through spatial weight matrices. This paper parameterizes each spatial weight matrix in the widely used spatial Durbin model with a different instead of one common distance decay parameter, using negative exponential and inverse distance matrices. We propose a joint estimation approach of the decay and response parameters, and we investigate its performance in a Monte Carlo simulation experiment. We also present the results of an empirical application on military expenditures. Indirect effects in particular appear to be sensitive to different parameterizations.

Based on the recent papers, two distributions for the total claims amount (loss cost) are considered: compound Poisson-gamma and Tweedie. Each is used as an underlying distribution in the Bonus-Malus Scale (BMS) model. The BMS model links the premium of an insurance contract to a function of the insurance experience of the related policy. In other words, the idea is to model the increase and the decrease in premiums for insureds who do or do not file claims. We applied our approach to a sample of data from a major insurance company in Canada. Data fit and predictability were analyzed. We showed that the studied models are exciting alternatives to consider from a practical point of view, and that predictive ratemaking models can address some important practical considerations.

Do the rich become more or less supportive of redistribution when exposed to poor people in their local surroundings? Most existing observational studies find that exposure to poor individuals is positively associated with support for redistribution among the well-off, but one prominent field experiment found a negative link. We seek to resolve these divergent findings by employing a design closer to the studies that have found a positive link, but with more causal leverage than these; specifically, a three-wave panel survey linked with fine-grained registry data on local income composition in Denmark. In within-individual models, increased exposure to poor individuals is associated with lower support for redistribution among wealthy individuals. By contrast, between-individual models yield a positive relationship, thus indicating that self-selection based on stable individual characteristics likely explains the predominant finding in previous work.

The purpose of this paper is to analyse the effects of natural resources on income inequality conditional on economic complexity in 111 developed and developing countries from 1995 to 2016. The system-GMM results show that economic complexity reverses the positive effects of natural resource dependence on income inequality. Furthermore, results are robust to the distinction between dependence on point resources (fossil fuels, ores, and metals), dependence on diffuse resources (agricultural raw material), and resource abundance. Finally, there are significant differences between countries, depending on the level of ethnic fragmentation and democracy.

Do negative economic shocks heighten public opposition to immigration, and through what mechanisms? Extant research suggests that economic circumstances and levels of labour market competition have little bearing on citizens' immigration attitudes. Yet personal economic shocks have the potential to trigger the threatened, anti-immigration responses – possibly through channels other than labour market competition – that prior cross-sectional research has been unable to detect. To examine these propositions, we used a unique panel study which tracked a large, population-based sample of Americans between 2007 and 2020. We found that adverse economic shocks, especially job losses, spurred opposition to unauthorized immigration. However, such effects are not concentrated among those most likely to face labour market competition from unauthorized immigrants. Instead, they are concentrated among white male Americans. This evidence suggests that the respondents' anti-immigration turn does not stem from economic concerns alone. Instead, personal experiences with the economy are refracted through salient socio-political lenses.

The purpose of this article is to assess the relationship between trade liberalisation in Tunisia and the employment intensity of sectoral output growth, in order to examine the claim that free trade creates jobs by stimulating growth. Using panel data for 15 Tunisian sectors over the period 1983–2010, we compare estimated sectoral output–employment elasticities prior to and following the Free Trade Agreement process with the European Union. The results provide evidence that trade liberalisation in Tunisia has led to an increase in the intensity of employment in exporting manufacturing sectors like textiles, clothing and leather industries, and mechanical and electrical industries. However, their ability to generate jobs in response to value-added growth remains weak. Conversely, since the Free Trade Agreement process, the most labour-intensive service sectors, notably tourism and miscellaneous services, have shown a significant decrease in the employment intensity of their output growth. Our findings suggest that the Free Trade Agreement with the European Union has not really fostered the shift of the Tunisian Economy towards a more inclusive model and support the argument for a reorientation of investment policy in favour of sectors generating more job opportunities.

We investigate the impact of five types of subsidies granted under the European Union Common Agricultural Policy on the persistent and transient inefficiency of Polish dairy farms. Our research shows that coupled and environmental subsidies reduce transient technical inefficiency, while the opposite is true for Less Favoured Areas (LFA) and other rural subsidies. Simultaneously, environmental, LFA, and other rural subsidies increase persistent technical inefficiency. These results imply that the impact of each type of subsidy on technical efficiency can be different and that the effect of the particular type of subsidy can vary between transient and persistent technical inefficiency.

The June 2016 Brexit referendum sent international shock waves, possibly causing adjustments in public opinion not only in the UK, but also abroad. We suggest that these adjustments went beyond substantive attitudes on European integration and included procedural preferences towards direct democracy. Drawing on the insight that support for direct democracy can be instrumentally motivated, we argue that the outcome of the Brexit referendum led (politically informed) individuals to update their support for referendums based on their views towards European integration. Using panel data from Germany, we find that those in favour of European integration, especially those with high political involvement, turned more sceptical of the introduction of referendums in the aftermath of the Brexit referendum. Our study contributes to the understanding of preferences for direct democracy and documents a remarkable case of how – seemingly basic – procedural preferences can, in today's internationalized information environment, be shaped by high-profile events abroad.

The violent conclusion of Trump's 2017–21 presidency has produced sobering reassessments of American democracy. Elected officials' actions necessarily implicate public opinion, but to what extent did Trump's presidency and its anti-democratic efforts reflect shifts in public opinion in prior years? Were there attitudinal changes that served as early-warning signs? We answer those questions via a fifteen-wave, population-based panel spanning 2007 to 2020. Specifically, we track attitudes on system legitimacy and election fairness, assessments of Trump and other politicians, and open-ended explanations of vote choice and party perceptions. Across measures, there was little movement in public opinion foreshadowing Trump's norm-upending presidency, though levels of out-party animus were consistently high. Recent shifts in public opinion were thus not a primary engine of the Trump presidency's anti-democratic efforts or their violent culmination. Such stability suggests that understanding the precipitating causes of those efforts requires attention to other actors, including activists and elites.

In recent papers, Bonus-Malus Scales (BMS) estimated using data have been considered as an alternative to longitudinal data and hierarchical data approaches to model the dependence between different contracts for the same insured. Those papers, however, did not discuss in detail how to construct and understand BMS models, and many of the BMS’s basic properties were not discussed. The first objective of this paper is to correct this situation by explaining the logic behind BMS models and by describing those properties. More particularly, we will explain how BMS models are linked with simple count regression models that have covariates associated with the past claims experience. This study could help actuaries to understand how and why they should use BMS models for experience rating. The second objective of this paper is to create artificial past claims history for each insured. This is done by combining recent panel data theory with BMS models. We show that this addition significantly improves the prediction capacity of the BMS and provides a temporary solution for insurers who do not have enough historical data. We apply the BMS model to real data from a major Canadian insurance company. Results are analysed deeply to identify specific aspects of the BMS model.

The relationship between social policy and inequality has often been contentious in Latin America. In this context, this article analysed the relationship between social spending and income inequality in the region in the short, medium, and long run. For this purpose, data on sixteen Latin American countries in the period 1990-2017 were gathered and analysed through a panel data study. The results showed that, in line with the findings at a global level, increased levels of overall social spending are indeed associated with reduced levels of income inequality in this region. However, each one of the four main areas of social spending were observed to have different effects on income inequality. Additionally, the results showed that, despite the reforms and the increases in budgets, the social protection and social services systems still have problems reaching those at the bottom of the income distribution in the region.

Credibility is elusive, but Blinder [(2000) American Economic Review 90, 1421–1431.] generated a consensus in the literature by arguing that “A central bank is credible if people believe it will do what it says.” To implement this idea, we first measure people’s beliefs by using survey data on inflation’s expectations. Second, we compare beliefs with explicit (or tacit) targets, taking into account the uncertainty in our estimate of beliefs (asymptotic 95% robust confidence intervals). Whenever the target falls into this interval we consider the central bank credible. We consider it not credible otherwise. We apply our approach to study the credibility of the Brazilian Central Bank (BCB) by using a world-class database—the Focus Survey of forecasts. Using monthly data from January 2007 until April 2017, we estimate people’s beliefs of inflation 12 months ahead, coupled with a robust estimate of its asymptotic 95% confidence interval. Results show that the BCB was credible 65% of the time, with the exception of a few months in the beginning of 2007 and during the interval between mid-2013 throughout mid-2016.

Telematicsdevices installed in insured vehicles provide actuaries with new risk factors, such as the time of the day, average speeds, and other driving habits. This paper extends the multivariate mixed model describing the joint dynamics of telematics data and claim frequencies proposed by Denuit et al. (2019a) by allowing for signals with various formats, not necessarily integer-valued, and by replacing the estimation procedure with the Expected Conditional Maximization algorithm. A numerical study performed on a database related to Pay-How-You-Drive, or PHYD motor insurance illustrates the relevance of the proposed approach for practice.

Using detailed spending and time use data from the Netherlands, this paper analyzes the causal effect of retirement on spending and time use decisions. Both total consumption and disaggregated consumption categories are considered. We do not find empirical evidence for drops in households' total non-durable spending at retirement. Our estimates suggest increases in spending at retirement on goods that are complementary to leisure, but no decreases in spending on goods that are replaceable by home production. The quantitative implication of our empirical results for the Life-Cycle Model is an intertemporal elasticity of substitution for leisure below unity.