Bayesian non-parametric signal extraction for Gaussian time series

We consider the problem of unobserved components in time series from a Bayesian non-parametric perspective. The identification conditions are treated as unknown and analyzed in a probabilistic framework. In particular, informative prior distributions force the spectral decomposition to be in an identifiable region. Then, the likelihood function adapts the prior decompositions to the data.     

Flexible Term Structure Estimation: Which Method is Preferred?

We show that the recently developed non-parametric procedure for fitting the term structure of interest rates developed by Linton, Mammen, Nielsen, and Tanggaard (J Econ 105(1):185–223, 2001) overall performs notably better than the highly flexible McCulloch (J Finon 30:811–830, 1975) cubic spline and Fama and Bliss (Am Econ Rev 77:680–692, 1987) bootstrap methods. However, if interest is limited to the Treasury-bill region alone then the Fama–Bliss method demonstrates superior performance. We further show, via simulation, that using the estimated short rate from the Linton–Mammen–Nielsen–Tanggaard procedure as a proxy for the short rate has higher precision then the commonly used proxies of the one and three month Treasury-bill rates. It is demonstrated that this precision is important when using proxies to estimate the stochastic process governing the evolution of the short rate     

Identification of volatility proxies as expectations of squared financial returns

Volatility proxies like realised volatility (RV) are extensively used to assess the forecasts of squared financial returns produced by volatility models. But are volatility proxies identified as expectations of the squared return? If not, then the results of these comparisons can be misleading, even if the proxy is unbiased. Here, a tripartite distinction is introduced between strong, semi-strong, and weak identification of a volatility proxy as an expectation of the squared return. The definition implies that semi-strong and weak identification can be studied and corrected for via a multiplicative transformation. Well-known tests can be used to check for identification and bias, and Monte Carlo simulations show that they are well sized and powerful—even in fairly small samples. As an illustration, 12 volatility proxies used in three seminal studies are revisited. Half of the proxies do not satisfy either semi-strong or weak identification, but their corrected transformations do. It is then shown how correcting for identification can change the rankings of volatility forecasts.     

Time-varying impact of monetary policy shocks on US stock returns: The role of investor sentiment

This paper investigates how monetary policy shock affects the stock market of the United States (US) conditional on states of investor sentiment. In this regard, we use a recently developed estimator that uses high-frequency surprises as a proxy for the structural monetary policy shocks, which in turn is achieved by integrating the current short-term rate surprises, which are least affected by an information effect, into a vector autoregressive (VAR) model as an exogenous variable. When allowing for time-varying model parameters, we find that, compared to the low investor sentiment regime, the negative reaction of stock returns to contractionary monetary policy shocks is stronger in the state associated with relatively higher investor sentiment. Our results are robust to alternative sample period (which excludes the zero lower bound) and model specification and also have important implications for academicians, investors, and policymakers.     

Asymptotics of the Non-parametric Function for B-splines-based Estimation in Partially Linear Models

We consider least squares method for partially linear models based on polynomial splines. We derive the asymptotic property for the estimator, focusing on the estimation of the non-parametric function, in particular whether and how the estimation of the linear part will affect the non-parametric part (the converse relation, that is, how the linear part will be affected by the non-parametric part is much better known, which we will also review). One important goal along the way is to clarify the role of projection in semiparametric models, which was nevertheless a classical trick for proving the asymptotic normality of the linear part. A crucial question we try to answer is whether projection plays any role in the estimation of the non-parametric function. The answer is both positive and negative depending on the direction along which to assess asymptotic normality. The style of writing of the paper is somewhat expository, and it also contains several new results not found in the current literature. Finally, we demonstrate in our numerical studies that construction of the pointwise confidence intervals for the non-parametric function motivated by our theory improves upon those constructed by pretending the linear part is known.     

Assessing the effects of U.S. shocks on the Canadian economy using alternative identification methods

This paper investigates the extent of the transmission of U.S. supply and demand shocks to the Canadian economy using three different identification methods. Our findings are robust across identifications. We show that over the flexible exchange rate period, U.S. shocks tend to intensify Canadian business cycles, while they reduce the mean of Canadian prices and inflation. We also find that overall Canadian output is less sensitive to U.S. disturbances than found in earlier studies. Moreover, when the structural shocks are allowed to be correlated across countries, Canadian shocks explain around 18% of U.S. real GDP growth long run forecast error variance.     

Economic Development and the Income of the Poor

A bstract . In their 1988 study of poverty Branco and Williamson suggested that the mean income of the poorest 40% of the population declines during the early stages of economic development. This result is, probably, due to the unusual indicator of economic development used by them (per capita energy consumption ). It is shown that if per capita income in "Real Purchasing Power Dollars" is used as a proxy for a country's level of development, the mean income of the poorest 40% is a monotonically increasing function of the level of economic development (although the mean income of particular socioeconomic groups may decline).     

Global financial uncertainty

We estimate a novel measure of global financial uncertainty (GFU) with a dynamic factor framework that jointly models global, regional, and country-specific factors. We quantify the impact of GFU shocks on global output with a VAR analysis that achieves set identification via a combination of narrative, sign, ratio, and correlation restrictions. We find that the contraction in world output during the Great Recession would have been 13% milder in absence of GFU shocks. We also find support for a global finance uncertainty multiplier: the more global financial conditions deteriorate after a GFU shock, the larger the world output contraction is.     

Measuring the Impact of Direct and Indirect R&D on the Productivity Growth of Industries: Using the Yale Technology Concordance

This paper investigates the impact of direct and indirect R&D on the productivity growth of 30 French industries during the period 1978–92. The main aim of this paper is to assess the appropriateness of the Yale Technology Concordance (YTC) as a proxy for indirect R&D flows. We compare the effect on productivity growth of the Yale proxy with the traditional proxy based on goods input–output flows, and assess their suitability for different groups of industries. Results indicate that the indirect YTC proxy performs slightly better than the traditional proxy, as a result of superior performance in the high-tech and service sectors in particular.     

Non- and semi-parametric estimation of interaction in inhomogeneous point patterns

We develop methods for analysing the 'interaction' or dependence between points in a spatial point pattern, when the pattern is spatially inhomogeneous. Completely non-parametric study of interactions is possible using an analogue of the K -function. Alternatively one may assume a semi-parametric model in which a (parametrically specified) homogeneous Markov point process is subjected to (non-parametric) inhomogeneous independent thinning. The effectiveness of these approaches is tested on datasets representing the positions of trees in forests.     

Guaranteed minimum income and unemployment duration in France

In this article, we use data from the European Community Household Panel to evaluate the impact of a French guaranteed income program, the RMI, on the hazard out of unemployment. Self-selection into the program is corrected using a multivariate duration model developed by [Abbring, J.H., van den Berg, G.J., 2003. The non-parametric identification of treatment effects in duration models. Econometrica 71 (5), 1491–1517]. We find that RMI receipt has a strong negative impact during the first months of program participation, but that this disincentive effect quickly falls to insignificant levels after six months. Household structure also appears to be an important determinant of the importance of the adverse effect of program participation.     

Estimation of firm-level productivity in the presence of exports: Evidence from China's manufacturing

Motivated by the long-standing interest of economists in understanding the nexus between firm productivity and export behavior, this paper develops a novel structural framework for control-function-based nonparametric identification of the gross production function and latent firm productivity in the presence of endogenous export opportunities that is robust to recent unidentification critiques of proxy estimators. We provide a workable identification strategy, whereby the firm's degree of export orientation provides the needed (excluded) relevant independent exogenous variation in endogenous freely varying inputs, thus allowing us to identify the production function. We estimate our fully nonparametric instrumental variable model using the Landweber–Fridman regularization with the unknown functions approximated via artificial neural network sieves with a sigmoid activation function, which are known for their superior performance relative to other popular sieve approximators, including the polynomial series favored in the literature. Using our methodology, we obtain robust productivity estimates for manufacturing firms from 28 industries in China during the 1999–2006 period to take a close look at China's exporter productivity puzzle, whereby exporters are found to exhibit lower productivity levels than nonexports.     

Macroeconomic Effects of Precautionary Demand for Oil

We evaluate the macroeconomic effects of shocks specific to the oil market, which mainly reflect fluctuations in precautionary demand for oil driven by uncertainty about future supplies. A two‐stage identification procedure is used. First, daily changes in the futures–spot price spread proxy for precautionary demand shocks and the path of oil prices is estimated. This information is then exploited to restrict the oil price response in a vector autoregression. Impulse responses suggest that such shocks reduce output and raise prices. Historical decomposition shows that they contributed significantly to the US recessions in the 1990s and in the early 2000s, but not to the most recent slump. Copyright © 2014 John Wiley & Sons, Ltd.     

Tender Offers, Proxy Contests, and Large-Shareholder Activism

The paper analyzes tender offers and proxy contests as alternative means of resolving corporate governance conflicts between dissidents and incumbent management. We show that when a dissident shareholder is sufficiently confident about the potential benefits from changing corporate policy, he will seek majority control by making a tender offer rather than initiating a proxy contest. When the dissident is relatively uninformed, however, he may opt for a proxy contest, thereby utilizing the information of other shareholders to implement the better policy. Consistent with empirical evidence, the model predicts that announcements of tender offers will tend to be associated with larger positive stockprice reactions than announcements of proxy contests. The model is easily extended to allow for promanagement bias in proxy voting by institutional investors. Empirical observations that have been viewed as evidence of such promanagement bias are shown to be quite consistent with the absence of such bias. Policy issues are discussed as well. An interesting result is that even policies targeted at reducing the costs of conducting proxy contests may have ambiguous social consequences, given the possibility of substitution between tender offers and proxy contests.     

Beta-product dependent Pitman–Yor processes for Bayesian inference

Multiple time series data may exhibit clustering over time and the clustering effect may change across different series. This paper is motivated by the Bayesian non-parametric modelling of the dependence between clustering effects in multiple time series analysis. We follow a Dirichlet process mixture approach and define a new class of multivariate dependent Pitman–Yor processes (DPY). The proposed DPY are represented in terms of vectors of stick-breaking processes which determine dependent clustering structures in the time series. We follow a hierarchical specification of the DPY base measure to account for various degrees of information pooling across the series. We discuss some theoretical properties of the DPY and use them to define Bayesian non-parametric repeated measurement and vector autoregressive models. We provide efficient Monte Carlo Markov Chain algorithms for posterior computation of the proposed models and illustrate the effectiveness of the method with a simulation study and an application to the United States and the European Union business cycle.     

基于因子分解的代理多重盲签名方案

代理多重签名是指两个以上的原始签名者将他们的签名权同时指派给一个代理签名者,代理签名者代表多个原始签名者实现他们的多重签名。盲签名是指签名人不知道所签消息的具体内容。文章结合代理多重签名和盲签名的优点,提出了一种新的签名方案,并对其有效性进行验证,最后指出进一步的研究方向。     

The impact of proxy contests on managerial turnover: A test of the job security hypothesis

This paper provides a test of the effect of proxy contests on managerial job security. We investigate senior executive turnover rates in the presence/absence of proxy fights associated with listed companies in Taiwan during the period 1984–91. The findings demonstrate that top management turnover is closely related to the incidence of proxy fights, lending support to the job security hypothesis.     

Geographical Proximity and Mutual Funds' Proxy Voting Behavior

This paper examines the influence of geographical proximity on mutual fund proxy voting decisions. Using mutual fund proxy voting data for the sample period July 1, 2003 to June 30, 2004, we find that fund managers vote more in favor of management of locally headquartered firms. The results are strong for proposals related to executive compensation, anti‐takeover provisions, social and political issues. We provide evidence to show that bias in proxy voting is not being driven by informational advantage; voting bias is prevalent in small as well as large size companies. Additionally, the voting pattern suggests that geographical proximity does not facilitate in better corporate monitoring as revealed in their voting decisions. We find that local fund managers vote more favorably in those proposals which do not increase shareholders' wealth and rights. Our results suggest that familiarity and social interaction between fund managers and firm executives located in the same geographic area might explain the local bias in mutual fund proxy voting behavior. Copyright © 2011 John Wiley & Sons, Ltd.     

Bayesian doubly adaptive elastic-net Lasso for VAR shrinkage

We develop a novel Bayesian doubly adaptive elastic-net Lasso (DAELasso) approach for VAR shrinkage. DAELasso achieves variable selection and coefficient shrinkage in a data-based manner. It deals constructively with explanatory variables which tend to be highly collinear by encouraging the grouping effect. In addition, it also allows for different degrees of shrinkage for different coefficients. Rewriting the multivariate Laplace distribution as a scale mixture, we establish closed-form conditional posteriors that can be drawn from a Gibbs sampler. An empirical analysis shows that the forecast results produced by DAELasso and its variants are comparable to those from other popular Bayesian methods, which provides further evidence that the forecast performances of large and medium sized Bayesian VARs are relatively robust to prior choices, and, in practice, simple Minnesota types of priors can be more attractive than their complex and well-designed alternatives.     

Interactive R&D spillovers: An estimation strategy based on forecasting-driven model selection

This paper proposes an estimation strategy that exploits recent non-parametric panel data methods that allow for a multifactor error structure and extends a recently proposed data-driven model-selection procedure, which has its roots in cross validation and aims to test whether two competing approximate models are equivalent in terms of their expected true error. We extend this procedure to a large panel data framework by using moving block bootstrap resampling techniques in order to preserve cross-sectional dependence in the bootstrapped samples. Such an estimation strategy is illustrated by revisiting an analysis of international technology diffusion. Model selection procedures clearly conclude in the superiority of a fully non-parametric (non-additive) specification over parametric and even semi-parametric (additive) specifications. This work also refines previous results by showing threshold effects, non-linearities, and interactions that are obscured in parametric specifications and which have relevant implications for policy.