Political Instability Equals the Collapse of Tourism in Ukraine?

The purpose of this study was to determine how political instability influences inbound tourist flows in Ukrainian cities, performance of tourism-related businesses, and tourism-based profits in general. This study allows us to present the impact of various events on the tourism economy in Ukraine; however, the available secondary data with the unobserved component model procedure detection give only a general overview of the situation. Thus, interviews were conducted with experts, including managers of accommodation facilities, employees of municipal tourism development departments, and researchers investigating tourism. Interviews with experts revealed opportunities, threats, and future scenarios of tourism in Ukraine in the face of five years of political instability. The results support previous findings that political instability reduces tourist traffic over the short term. On the other hand, the interviews with experts representing major province cities have shown different results for the long-term perspective. Cities with developed tourism sectors in areas away from the place of conflict are beneficiaries of political instability. Disadvantaged are cities that had their tourist flows based on the citizens of the aggressor’s country—the Russian Federation. Cities that are underdeveloped in terms of tourism did not experience a significant impact of the political instability in eastern Ukraine.

Evidence of Neighborhood Effects from Moving to Opportunity: Lates of Neighborhood Quality

This paper estimates neighborhood effects on adult labor market outcomes using the Moving to Opportunity (MTO) housing mobility experiment. We propose and implement a new strategy for identifying transition-specific effects that exploits identification of the unobserved component of a neighborhood choice model. Estimated local average treatment effects (LATEs) are large, result from moves between the first and second deciles of the national distribution of neighborhood quality, and pertain to a subpopulation of nine percent of program participants.

The fiscal policy and the dynamic of the economic cycle

PurposeThis study seeks to determine in some detail whether the state of the economic cycle matters in considering the effects of fiscal policy shocks on output.Design/methodology/approachThis issue leads us to two primary objectives: to define the economic cycle measuring the gap with the unobserved component model with a smoother trend, which can be used efficiently to generate gap measures for use in real-time decision-making and avoids the criticisms of measures based on contentious structural models; and to look empirically at the fiscal policy stance over the phases of the cycle, bearing in mind the short time variation and smooth change between the cycle regimes.FindingsThis paper provides evidence that the fiscal policy rule seems to operate with varied coefficients depending on whether the transition variable is below or above the estimated threshold value.Originality/valueThe asymmetric response gives policymakers the impetus to reconsider the fiscal policy framework because of specific circumstances, such as shocks that can dramatically affect the nominal features of the business cycle. Put differently, stable and moderate fiscal policies would at least not contribute to cyclical fluctuations, and therefore would be better than what we have typically experienced. There would, therefore, seem to be a distinct need to address the properties of economic cycles under different fiscal policy rules.

An effcient exact Bayesian method For state space models with stochastic volatility

This paper introduces a Bayesian MCMC method, referred to as a marginalized mixture sampler, for state space models whose disturbances follow stochastic volatility processes. The marginalized mixture sampler is based on a mixture-normal approximation of the log-χ2 distribution, but it is implemented without the need to simulate the mixture indicator variable. The key innovation is to use the filter ing scheme developed by Kim (Kim C.-J. 1994. “Dynamic Linear Models with Markov-Switching.” Journal of Econometrics 60: 1–22.) and the forward-filtering backward-sampling algorithm to generate a proposal series of the latent stochastic volatility process. The proposal series is then accepted according to the Metropolis-Hastings acceptance probability. The new sampler is examined within an unobserved component model and a time-varying parameter vector autoregressive model, and it reduces substantially the correlations between MCMC draws.

Assessing Robustness of Asian Countries Ranking

The term ‘digital divide' refers to the gap between individuals, households, businesses and geographic areas with regard to both their opportunities to access Information and Communication Technologies (ICT) and to their use of Internet. Composite indicators are regularly used for measuring the divide and in benchmarking the country's performance. But often it creates controversies regarding the subjectivity that is connected with their construction methodology more specifically the weighting and aggregation issues. The paper attempts to assess the robustness of the ranks generated by the composite digital divide index using different weighting and aggregation schemes in case of Asian countries. Here four weighting techniques Iyengar-Sudarshan Method, Benefit of Doubt Method, Principal Component Analysis and Unobserved Component Model and three techniques of aggregation viz. Linear Aggregation, Geometric Aggregation and Weighted Displaced Ideal Method are used for mutual comparison.