Modified efficient importance sampling for partially non‐Gaussian state space models

The construction of an importance density for partially non‐Gaussian state space models is crucial when simulation methods are used for likelihood evaluation, signal extraction, and forecasting. The method of efficient importance sampling is successful in this respect, but we show that it can be implemented in a computationally more efficient manner using standard Kalman filter and smoothing methods. Efficient importance sampling is generally applicable for a wide range of models, but it is typically a custom‐built procedure. For the class of partially non‐Gaussian state space models, we present a general method for efficient importance sampling. Our novel method makes the efficient importance sampling methodology more accessible because it does not require the computation of a (possibly) complicated density kernel that needs to be tracked for each time period. The new method is illustrated for a stochastic volatility model with a Student's t distribution.     

Research collaboration model in academic social networks

ABSTRACT

This paper proposes a hybrid collaboration recommendation method that accounts for research similarities and the previous research cooperation network. Research cooperation is measured by combining the collaboration time and the number of co-authors who already collaborated with at least one scientist. Research similarity is based on authors’ previous publications and academic events they attended. A weighted directed graph is built to discover new collaborators by using direct and indirect connections between scientists. Moreover, a consensus-based system is built to integrate bibliography data from different sources. The experimental results show that our method improves the recommendation performances over other methods.     

ALTERNATIVE WEIGHTING APPROACHES TO COMPUTING INDEXES OF ECONOMIC ACTIVITY

This paper compares the weighting schemes in the traditional, principal component and dynamic factor approaches to summarizing information from a number of component variables. To facilitate the comparison, we propose a framework to discuss the approaches with respect to their implied loadings in a latent variable model. We also propose a way to transform the dynamic factor index into an analogous index which is a weighted average of the components. The framework shows the strengths and weakness of the alternative weighting schemes and the sense in which the dynamic factor approach has the advantage of capturing both the significance and the variability of the components.     

The impact of governance and transparency on firm investment in Vietnam

A large literature asserts a causal relationship between the quality of economic governance and economic performance. However, attempts to establish such a link at an aggregate level have met with considerable methodological criticism. This paper seeks to overcome this limitation. We match a panel of Vietnamese enterprises from 2006 to 2010 with a unique panel dataset measuring sub‐national economic governance to estimate a relationship between local governance and private investment. We do not find a significant relationship between investment and most traditional forms of governance. However, there is one important exception – transparency, especially the public posting of planning documents, is strongly associated with higher investment across a range of different specifications. Our results have significant implications for policy, given the prevailing theory that changes in the quality of local economic governance will spur improved economic performance.     

Drivers of firm formalization in Vietnam: an attention theory explanation

Informal enterprises are widely viewed as a mechanism to engage unemployed people in the economy and thereby alleviate poverty in developing economies. However, over-representation in an economy may lead to both economic growth and broader employment opportunities being sacrificed. This paper presents a process model to investigate three potential drivers for firms to formalize: the first from a desire to grow and develop the firm through innovation, the second from the wish to access government financial support and the third stimulated by the payment of unofficial payments or bribes. We use data from surveys of Vietnamese firms in 2005, 2007, 2009 and 2011 to investigate these drivers of formalization. Although we find support for all three of these drivers, the results differ in significance across years and firm types. We explain these differences using attention theory to show how different situations and events can make the formalization decision more likely over time.     

Characterizations of negative multinomial distributions based on conditional distributions

In this paper characterizations of negative multinomial distributions based on conditional distributions have been studied.     

Characterization of Normal Distribution Related to Two Samples Based on Regression

Characterization of normal distribution related to two samples based on second conditional moments has been obtained. This characterization has been transformed to a characterization based on the UMVU estimators of the density function. These results are generalized to k samples from normal distributions. Finally applications of these characterization results to goodness-of-fit test are discussed.     

Inter-market competition for exchange traded funds

We examine how the different mix of informed and liquidity trading in the market for ETFs affects the nature of inter-market competition. We find that both the characteristics of the securities and the structures of the competing markets jointly determine the nature of inter-market competition. Given the superior execution quality on the ECNs and the low adverse selection costs in the ETF market, anonymous market such as the ECNs, attract both liquidity and informed traders. We also find that markets compete in a subset of ETFs. In addition, we find that quotebased competition is prevalent in the market for ETFs.     

Assessing the impacts of oil price fluctuations on stock returns in emerging markets

This paper investigates the effects of oil price shocks on stock market returns in emerging countries. It differs from previous works in three main aspects: i) we distinguish three groups of countries, the largest net-oil importing countries, the moderately oil-dependent countries, and the largest net-oil exporting countries; ii) The potential influence of bullish and bearish market conditions on the causal relationship between oil and stock returns is controlled for in our analysis; iii) The empirical investigation is based on an analysis of long-term correlation and a conditional multifactor pricing model. Using data from twenty-five emerging countries, our results suggest that oil price risk is significantly priced in emerging markets, and that the oil impact is asymmetric with respect to market phases.