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AbstractThis paper investigates the impact of social media interest and sentiment surrounding the 2020 National Basketball Association's involvement with the Black Lives Matter movement on the television audience in the United States. Twitter (now known as X) serves as the chosen social media platform, and we determine the sentiment expressed in tweets (messages posted on Twitter) using the XLM-RoBERTa deep language model. Our primary findings indicate that the quantity of users' posts does not significantly influence TV viewership; instead, the tone of the messages plays a crucial role. Positive messages supporting the NBA's engagement correlate with an increase in the number of viewers, while those expressing opposition do not. We argue that this asymmetry may stem from a positive elasticity among casual (non-habitual) NBA viewers concerning positive sentiments toward NBA involvement. These viewers are likely to align with the NBA's stances on civil rights and BLM. In contrast, the core NBA fan base exhibits inelastic demand and is unlikely to cease watching NBA games. A comprehensive set of robustness checks reinforces the validity of our key conclusions.

AbstractRecent years have witnessed a growing aversion to immigration worldwide and, at the same time, radicalization of public opinion on the issue. This paper explores the relationship between media news and individual attitudes to immigration. We run an empirical analysis whereby an index capturing individuals' pro-immigration attitude, measured in 19 countries, is regressed over indexes capturing the coverage and tone of media news about immigration. We find that pro-immigration attitudes are negatively correlated with media coverage and the negative tone of news. However, this correlation is significant only for those with high trust in the media. In the case of low trust, higher coverage of immigration and a negative news slant make previous preferences and beliefsvis-à-visimmigration more extreme, yielding a lower pro-immigration index for those politically on the right, while the opposite applies to those on the left. The pro-immigration index is constructed by means of fuzzy methods to account for the many aspects defining attitudes to immigration.

Ce travail examine les effets du terrorisme sur la croissance économique en Inde. En utilisant un modèle de Markov à changement de régime, on trouve des preuves que le terrorisme a des effets importants et négatifs sur la croissance économique de l'Inde. Nos résultats empiriques montrent aussi que l'ampleur de ces effets est plus grande dans des périodes de haute croissance économique. Enfin, nous comparons l'ampleur des effets de « brutalité » et de « fréquence » des attaques terroristes et nous concluons que l'effet de « fréquence » est légèrement plus élevé que l'effet de « brutalité ». JEL Classification: C32, E2.

© 2015 The Authors. This paper estimates the magnitudes of government spending and tax multipliers within a regime-switching framework for the U.S. economy during the period 1949:1-2006:4. Our results show that the magnitudes of spending multipliers are larger during periods of low economic activity, while the magnitudes of tax multipliers are larger during periods of high economic activity. We also show that the magnitudes of fiscal multipliers got smaller for episodes of low growth, while they got larger for episodes of high growth in the post 1980 period. Analyzing the effects of government spending and taxes on consumption and investment spending indicates that the magnitude of the effects of fiscal shocks on consumption and investment is very small.