Bayesian analysis of coefficient instability in dynamic regressions

This paper proposes a Bayesian regression model with time-varying coefficients (TVC) that makes it possible to estimate jointly the degree of instability and the time-path of regression coefficients. Thanks to its computational tractability, the model proves suitable to perform the first (to our knowledge) Monte Carlo study of the finite-sample properties of a TVC model. Under several specifications of the data generating process, the proposed model’s estimation precision and forecasting accuracy compare favourably with those of other methods commonly used to deal with parameter instability. Furthermore, the TVC model leads to small losses of efficiency under the null of stability and it is robust to mis-specification, providing a satisfactory performance also when regression coefficients experience discrete structural breaks. As a demonstrative application, we use our TVC model to estimate the exposures of S&P 500 stocks to market-wide risk factors: we find that a vast majority of stocks have time-varying risk exposures and that the TVC model helps to forecast these exposures more accurately.time-varying regression, coefficient instability

Exports and productivity selection effects for Dutch firms

The paper investigates whether the self-selection hypothesis and other predictions from the heterogeneous-firms trade models can explain the export participation patterns for Dutch firms in manufacturing and services. The results provide strong support for the self-selection hypothesis, according to which firms need higher productivity performance to compensate for sunk entry costs in export markets. After controlling for many firm and market characteristics we robustly find higher productivity levels for exporters. The paper also tests for the reverse causality (learning-by-exporting), but finds no empirical support for it, not even after controlling for the firm's distance to a constructed international productivity frontier. This latter result may be important for the motivation of future export promotion policies. The empirical estimates are achieved by probit regressions at the plant level and at the firm level. As a robustness test we also applied the more standard OLS panel regression estimates, which provided similar results. The paper also tested whether the productivity-export link is conditional on the sectoral market structure and multinational affiliation. Services sectors with high competition and a lower degree of product differentiation have significantly higher export productivity premia than services firms in less competitive sectors. Such differences are not found in the manufacturing sector.Export participation, productivity, self selection, market structure

Vertical integration and firm boundaries : the evidence

Since Ronald H. Coase's (1937) seminal paper, a rich set of theories has been developed that deal with firm boundaries in vertical or input–output structures. In the last twenty-five years, empirical evidence that can shed light on those theories also has been accumulating. We review the findings of empirical studies that have addressed two main interrelated questions: First, what types of transactions are best brought within the firm and, second, what are the consequences of vertical integration decisions for economic outcomes such as prices, quantities, investment, and profits. Throughout, we highlight areas of potential cross-fertilization and promising areas for future work

Why are Prices Sticky? Evidence from Business Survey Data

This paper offers new insights on the price setting behaviour of German retail firms using a novel dataset that consists of a large panel of monthly business surveys from 1991-2006. The firm-level data allows matching changes in firms' prices to several other firm-characteristics. Moreover, information on price expectations allow analyzing the determinants of price updating. Using univariate and bivariate ordered probit specifications, empirical menu cost models are estimated relating the probability of price adjustment and price updating, respectively, to both time- and state- dependent variables. First, results suggest an important role for state-dependence; changes in the macroeconomic and institutional environment as well as firm-specific factors are significantly related to the timing of price adjustment. These findings imply that price setting models should endogenize the timing of price adjustment in order to generate realistic predictions concerning the transmission of monetary policy. Second, an analysis of price expectations yields similar results providing evidence in favour of state-dependent sticky plan models. Third, intermediate input cost changes are among the most important determinants of price adjustment suggesting that pricing models should explicitly incorporate price setting at different production stages. However, the results show that adjustment to input cost changes takes time indicating "additional stickiness" at the last stage of processing

DSGE model-based forecasting of non-modelled variables

This paper develops and illustrates a simple method to generate a DSGE model-based forecast for variables that do not explicitly appear in the model (non-core variables). The authors use auxiliary regressions that resemble measurement equations in a dynamic factor model to link the non-core variables to the state variables of the DSGE model. Predictions for the non-core variables are obtained by applying their measurement equations to DSGE model- generated forecasts of the state variables. Using a medium-scale New Keynesian DSGE model, the authors apply their approach to generate and evaluate recursive forecasts for PCE inflation, core PCE inflation, and the unemployment rate along with predictions for the seven variables that have been used to estimate the DSGE model.Forecasting

Deducing the Multi-Trader Population Driving a Financial Market

We previously laid out a framework for predicting financial movements and pockets of predictability by deducing the heterogeneity in the multi-agent population in temrs of trader types playing in an artificial financial market model [7]. This work explores extensions to this basic framework. We allow for more intelligent agents with a richer strategy set, and we no longer constrain the estimate for the heterogeneity over the agents to a probability space. We then introduce a scheme which accounts for models with a wide variety of agent types. We also discuss a mechanism for bias removal on the estimates of the relevant parameters

Smart Meter Devices and The Effect of Feedback on Residential Electricity Consumption: Evidence from a Natural Experiment in Northern Ireland

Using a unique set of data and exploiting a large-scale natural experiment, we estimate the effect of real-time usage information on residential electricity consumption in Northern Ireland. Starting in April 2002, the utility replaced prepayment meters with “smart” meters that allow the consumer to track usage in real-time. We rely on this event, account for the endogeneity of price and plan with consumption through a plan selection correction term, and find that the provision of information is associated with a decline in electricity consumption of up to 20%. We find that the reduction is robust to different specifications, selection-bias correction methods and subsamples of the original data. At £15-17 per tonne of CO2e (2009£), the smart meter program delivers cost-effective reductions in carbon dioxide emissions.Residential Energy, Electricity Demand, Feedback, Smart Meter, Information