Distributional and Poverty Consequences of Globalization: A Dynamic Comparative Analysis for Developing Countries

This study examines the impact of globalization on cross-country inequality and poverty using a panel data set for 65 developing counties, over the period 1970-2008. With separate modelling for poverty and inequality, explicit control for financial intermediation, and comparative analysis for developing countries, the study attempts to provide a deeper understanding of cross country variations in income inequality and poverty. The major findings of the study are five fold. First, a non-monotonic relationship between income distribution and the level of economic development holds in all samples of countries. Second, both openness to trade and FDI do not have a favourable effect on income distribution in developing countries. Third, high financial liberalization exerts a negative and significant influence on income distribution in developing countries. Fourth, inflation seems to distort income distribution in all sets of countries. Finally, the government emerges as a major player in impacting income distribution in developing countries.

Forecasting Inflation Using Dynamic Model Averaging

We forecast quarterly US inflation based on the generalized Phillips curve using econometric methods which incorporate dynamic model averaging. These methods not only allow for coe¢ cients to change over time, but also allow for the entire forecasting model to change over time. We nd that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and more sophisticated approaches such as those using time varying coe¢ cient models. We also provide evidence on which sets of predictors are relevant for forecasting in each period.

Forecasting Inflation Using Dynamic Model Averaging

We forecast quarterly US inflation based on the generalized Phillips curve using econometric methods which incorporate dynamic model averaging. These methods not only allow for coe¢ cients to change over time, but also allow for the entire forecasting model to change over time. We nd that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and more sophisticated approaches such as those using time varying coe¢ cient models. We also provide evidence on which sets of predictors are relevant for forecasting in each period.

Alliance evolutions over the course of short-term dynamic psychotherapy: A case study

Background: Alliance evolutions, i.e. ruptures and resolutions over the course of psychotherapy, have been shown to be important descriptive features in different forms of psychotherapy, and in particular in psychodynamic psychotherapy. This case study of a client presenting elements of adjustment disorder undergoing short-term dynamic psychotherapy is drawn from a systematic naturalistic study and aims at illustrating, on a session-by-session-level, the processes of alliance ruptures and resolutions, by comparing both the client's and the therapist's perspectives. Method: Two episodes of alliance evolution were more fully studied, in relation to the evolution of transference, as well as the client's defensive functioning and core conflictual theme. These concepts were measured by means of valid, reliable observer-rater methods, based on session transcripts: the Defense Mechanisms Rating Scales (DMRS) for defensive functioning and the Core Conflictual Relationship Theme (CCRT) for the conflicts. Alliance was measured after each session using the Helping Alliance questionnaire (HAq-II). Results: The results indicated that these episodes of alliance rupture and resolutions may be understood as key moments of the whole therapeutic process reflecting the client's main relationship stakes. Illustrations are provided based on the client's in-session processes and related to the alliance development over the course of the entire therapy.

Co-movements in Real Effective Exchange Rates: Evidence from the Dynamic Hierarchical Factor Model

We analyze and quantify co-movements in real effective exchange rates while considering the regional location of countries. More specifically, using the dynamic hierarchical factor model (Moench et al. (2011)), we decompose exchange rate movements into several latent components; worldwide and two regional factors as well as country-specific elements. Then, we provide evidence that the worldwide common factor is closely related to monetary policies in large advanced countries while regional common factors tend to be captured by those in the rest of the countries in a region. However, a substantial proportion of the variation in the real exchange rates is reported to be country-specific; even in Europe country-specific movements exceed worldwide and regional common factors.

A Simple Characterization of Dynamic Completeness in Continuous Time

This paper investigates dynamic completeness of financial markets in which the underlying risk process is a multi-dimensional Brownian motion and the risky securities dividends geometric Brownian motions. A sufficient condition, that the instantaneous dispersion matrix of the relative dividends is non-degenerate, was established recently in the literature for single-commodity, pure-exchange economies with many heterogenous agents, under the assumption that the intermediate flows of all dividends, utilities, and endowments are analytic functions. For the current setting, a different mathematical argument in which analyticity is not needed shows that a slightly weaker condition suffices for general pricing kernels. That is, dynamic completeness obtains irrespectively of preferences, endowments, and other structural elements (such as whether or not the budget constraints include only pure exchange, whether or not the time horizon is finite with lump-sum dividends available on the terminal date, etc.)

Complete Markets Strikes Back: Revisiting Risk Sharing Tests under Discount Rate Heterogeneity

Recent risk sharing tests strongly reject the hypothesis of complete markets, because in the data: (1) the individual consumption comoves with income and (2) the consumption dispersion increases over the life cycle. In this paper, I revisit the implications of these risk sharing tests in the context of a complete market model with discount rate heterogeneity, which is extended to introduce the individual choices of effort in education. I .nd that a complete market model with discount rate heterogeneity can pass both types of the risk sharing tests. The endogenous positive correlation between income growth rate and patience makes the individual consumption comove with income, even if the markets are complete. I also show that this model is quantitatively admissible to account for both the observed comovement of consumption and income and the increase of consumption dispersion over the life cycle.

Modeling Dependence Structure and Forecasting Portfolio Value-at-Risk with Dynamic Copulas

We study the asymmetric and dynamic dependence between financial assets and demonstrate, from the perspective of risk management, the economic significance of dynamic copula models. First, we construct stock and currency portfolios sorted on different characteristics (ex ante beta, coskewness, cokurtosis and order flows), and find substantial evidence of dynamic evolution between the high beta (respectively, coskewness, cokurtosis and order flow) portfolios and the low beta (coskewness, cokurtosis and order flow) portfolios. Second, using three different dependence measures, we show the presence of asymmetric dependence between these characteristic-sorted portfolios. Third, we use a dynamic copula framework based on Creal et al. (2013) and Patton (2012) to forecast the portfolio Value-at-Risk of long-short (high minus low) equity and FX portfolios. We use several widely used univariate and multivariate VaR models for the purpose of comparison. Backtesting our methodology, we find that the asymmetric dynamic copula models provide more accurate forecasts, in general, and, in particular, perform much better during the recent financial crises, indicating the economic significance of incorporating dynamic and asymmetric dependence in risk management.

Modeling Dependence Structure and Forecasting Market Risk with Dynamic Asymmetric Copula

We investigate the dynamic and asymmetric dependence structure between equity portfolios from the US and UK. We demonstrate the statistical significance of dynamic asymmetric copula models in modelling and forecasting market risk. First, we construct “high-minus-low" equity portfolios sorted on beta, coskewness, and cokurtosis. We find substantial evidence of dynamic and asymmetric dependence between characteristic-sorted portfolios. Second, we consider a dynamic asymmetric copula model by combining the generalized hyperbolic skewed t copula with the generalized autoregressive score (GAS) model to capture both the multivariate non-normality and the dynamic and asymmetric dependence between equity portfolios. We demonstrate its usefulness by evaluating the forecasting performance of Value-at-Risk and Expected Shortfall for the high-minus-low portfolios. From back-testing, e find consistent and robust evidence that our dynamic asymmetric copula model provides the most accurate forecasts, indicating the importance of incorporating the dynamic and asymmetric dependence structure in risk management.

Estimation of dynamic latent variable models using simulated nonparametric moments

Abstract. Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the parameter. Because conditional moments are calculated using kernel smoothing rather than simple averaging, it is not necessary that the model be simulable subject to the conditioning information that is used to define the moment conditions. For this reason, the proposed estimator is applicable to general dynamic latent variable models. It is shown that as the number of simulations diverges, the estimator is consistent and a higher-order expansion reveals the stochastic difference between the infeasible GMM estimator based on the same moment conditions and the simulated version. In particular, we show how to adjust standard errors to account for the simulations. Monte Carlo results show how the estimator may be applied to a range of dynamic latent variable (DLV) models, and that it performs well in comparison to several other estimators that have been proposed for DLV models.

In vitro growth of human urinary tract smooth muscle cells on laminin and collagen type I-coated membranes under static and dynamic conditions.

This study investigates in vitro growth of human urinary tract smooth muscle cells under static conditions and mechanical stimulation. The cells were cultured on collagen type I- and laminin-coated silicon membranes. Using a Flexcell device for mechanical stimulation, a cyclic strain of 0-20% was applied in a strain-stress-time model (stretch, 104 min relaxation, 15 s), imitating physiological bladder filling and voiding. Cell proliferation and alpha-actin, calponin, and caldesmon phenotype marker expression were analyzed. Nonstretched cells showed significant better growth on laminin during the first 8 days, thereafter becoming comparable to cells grown on collagen type I. Cyclic strain significantly reduced cell growth on both surfaces; however, better growth was observed on laminin. Neither the type of surface nor mechanical stimulation influenced the expression pattern of phenotype markers; alpha-actin was predominantly expressed. Coating with the extracellular matrix protein laminin improved in vitro growth of human urinary tract smooth muscle cells.

Dynamic of population-dynamics in a medically important snail species Lymnaea (Radix) Luteola (Lamarck)

The life-cycle parameters of the snail Lymnaea (Radix) luteola and the factors influencing the same have been studied under laboratory conditions. Ins each month, from July 1990 to June 1991, a batch of 100 zero-day old individual were considered for studies. The snails of April batch survived for 19.42 days while those in December batch survived for 87.45 days. The May batch individual though survived for 65.67 days gained maximum shell size (15.84 mm in length) and body weight (419.87 mg). All individuals of April batch died prior to attainment of sexual maturity. In the remaining 11 batches the snails became sexually mature between 32 and 53 days. At this stage, they were with varying shell lengths, 9.3 mm to 13,11 mm in respect to batches. The reproduction period varied from 1-67 days. An individual laid, on an average, 0,25 (March batch) to 443.67 (May batch) eggs in its life-span. A batch of such snails would leave 24312, 22520, 720268, 80408, 76067, 418165, 214, 9202, 0, 0, 2459386 and 127894 individuals at the end of 352nd day. Since the environmental conditions were almost similar the 'dynamic' of population dynamics seems to be involved with the 'strain' of the snail individuals of the batches concerned.

Investor protection and income inequality: risk sharing vs risk taking

This paper studies the relationship between investor protection, entrepreneurial risk taking and income inequality. In the presence of market frictions, better protection makes investors more willing to take on entrepreneurial risk when lending to firms, thereby improving the degree of risk sharing between financiers and entrepreneurs. On the other hand, by increasing risk sharing, investor protection also induces more firms to undertake risky projects. By increasing entrepreneurial risk taking, it raises income dispersion. By reducing the risk faced by entrepreneurs, it reduces income volatility. As a result, investor protection raises income inequality to the extent that it fosters risk taking, while it reduces it for a given level of risk taking. Empirical evidence from a panel of forty-five countries spanning the period 1976-2000 supports the predictions of the model.

Dynamic calibration of our sense of time.

An accurate sense of time contributes to functions ranging from the perception and anticipation of sensory events to the production of coordinated movements. However, accumulating evidence demonstrates that time perception is subject to strong illusory distortion. In two experiments, we investigated whether the subjective speed of temporal perception is dependent on our visual environment. By presenting human observers with speed-altered movies of a crowded street scene, we modulated performance on subsequent production of "20s" elapsed intervals. Our results indicate that one's visual environment significantly contributes to calibrating our sense of time, independently of any modulation of arousal. This plasticity generates an assay for the integrity of our sense of time and its rehabilitation in clinical pathologies.