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I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypotheses formulated in light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

Urbanisation, environmental sustainability and property markets are intertwined. Consequently, studies on any of these three topics need to take the other two topics into consideration. By critically reviewing 33 hedonic pricing studies in 16 key journals in the urban studies and environmental policies areas, we summarise quantitative evidence on the price of environmental externalities resulting from China's urbanisation process. We find that Chinese residents are willing to pay more for the access to green space and waterbody as well as the treatment of urban pollution. The cost and benefit of these amenities and disamenities have already been capitalised in house prices. The central and local government in China can leverage market force to encourage, support and facilitate sustainable urban development and environmental protection, instead of directly intervening in the property market by using public resources. Meanwhile, the estimated hedonic price of Urban Green, Urban Blue and Urban Grey helps policymakers to understand the cost and benefit of their urban development decisions. Our review of the papers on Urban Green, Urban Blue and Urban Grey suggests that there have been promising and encouraging development in studies on all three topics in the last decade. The quality and quantity of hedonic price research has been improving notably. However, it is also clear that there is virtually no empirical evidence from the second- or third-tier cities, particularly, regarding Urban Green and Urban Blue investigations. The small number of existing hedonic studies is far from sufficient to draw reliable conclusions about the costs of environmental externality for cities that have not been studied. What works in first-tier cities may not hold elsewhere in China due to the large geographical variation in natural endowment, economic development status and local customs. There are many pieces that are missing from this big picture. More hedonic price studies are needed.

We test the determinacy properties of the standard and financial-sector-augmented Taylor rules in a new Keynesian model with a presence of banking activities. We extend the basic fully rational environment to the setting with heterogeneous expectations. We observe that the benefits from extra financial targeting are limited. Financial targeting, if well designed, can compensate for the improper output-gap targeting through the financial-production channel. The analysis demonstrates however possible threats resulting from the misspecification of the augmented rule. A determinate mix of output-gap and inflation weights can turn indeterminate if compensated by too extreme financial targeting. The results are robust to the presence of heterogeneous expectations.

I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models have to fit financial time series and at the same time provide powerful tools to test hypotheses formulated in the light of financial theories, and to generate positive economic value, as measured by risk-adjusted performances, in dynamic asset allocation applications. The chapter also reviews the role of Markov switching dynamics in modern asset pricing models in which the no-arbitrage principle is used to characterize the properties of the fundamental pricing measure in the presence of regimes.

Transient climate sensitivity relates total climate forcings from anthropogenic and other sources to surface temperature. Global transient climate sensitivity is well studied, as are the related concepts of equilibrium climate sensitivity (ECS) and transient climate response (TCR), but spatially disaggregated local climate sensitivity (LCS) is less so. An energy balance model (EBM) and an easily implemented semiparametric statistical approach are proposed to estimate LCS using the historical record and to assess its contribution to global transient climate sensitivity. Results suggest that areas dominated by ocean tend to import energy, they are relatively more sensitive to forcings, but they warm more slowly than areas dominated by land. Economic implications are discussed.

This paper compares the predictive power of linear econometric and non-linear computational models for forecasting the inflation rate in the European Monetary Union (EMU). Various models of both types are developed using different monetary and real activity indicators. They are compared according to a battery of parametric and non-parametric test statistics to measure their performance in one- and four-step ahead forecasts of quarterly data. Using genetic-neural fuzzy systems we find the computational approach superior to some degree and show how to combine both techniques successfully.

We estimate a double-hurdle (DH) model of the Hungarian wage distribution assuming censoring at the minimum wage and wage under-reporting (i.e. compensation consisting of the minimum wage, subject to taxation and an unreported cash supplement). We estimate the probability of under-reporting for minimum wage earners, simulate their genuine earnings and classify them and their employers as ‘cheaters’ and ‘non-cheaters’. In the possession of the classification, we check how cheaters and non-cheaters reacted to the introduction of a minimum social security contribution base, equal to 200 per cent of the minimum wage, in 2007. The findings suggest that cheaters were more likely to raise the wages of their minimum wage earners to 200 per cent of the minimum wage, thereby reducing the risk of tax audit. Cheating firms also experienced faster average wage growth and slower output growth. The results suggest that the DH model is able to identify the loci of wage under-reporting with some precision.