Rolling Regression Analysis of the Pástor-Stambaugh Model: Evidence from Robust Instrumental Variables

The capital asset pricing model (CAPM), Fama-French (FF), and Pástor-Stambaugh (PS) factor models are examined using a new dynamic rolling regression version of the generalized method of moments (GMM) method. This rolling regression framework not only allows us to investigate phases of the business cycle, but also permits regression estimates to vary through time due to changes in the development and efficiency of the sectors. The principal reasons for using the dynamic GMM with robust instruments is that some of these factors are measured with errors and the disturbances may be non-spherical. The CAPM appears as the most parsimonious model to explain the FF sector returns. Furthermore, the rolling GMM approach is clearly more sensitive to dynamic financial episodes than the ordinary least squares approach. In particular, liquidity has some anticipatory power, as it is able to forecast the 2007–2009 crises with heightened volatility starting in late 2005.     

POLITICAL SELECTION OF FIRMS INTO PRIVATIZATION PROGRAMS. EVIDENCE FROM ROMANIAN COMPREHENSIVE DATA

Exploiting a unique institutional feature of early Romanian privatization, when a group of firms was explicitly barred from privatization and another was partially privatized by management–employee buyouts, we test how politicians select firms into privatization programs. Using comprehensive firm data, we estimate the relation between preprivatization firm characteristics – the information known to politicians at the time of decision‐making – and the effect of privatization on employment, efficiency, and wages. With the estimated coefficients we simulate the effect of privatization on non‐privatizable and privatizable firms. We find that politicians expected privatization to increase employment in the privatizable group by 7%–10%, while to decrease it in the non‐privatizable group by 10%–30%, depending on the first‐stage estimation method, ordinary least squares with or without matching. We do not find such discrepancies in the expected change in firm efficiency; the simulated efficiency effect of privatization is large and positive for both groups of firms, and it is 52%–65% for non‐privatizable and 41%–43% for privatizable firms. The analysis does not support the hypothesis that wages played an important role in privatization decisions. Our study suggests that employment concerns played the key role in selecting firms for privatization, even if efficiency gains had to be sacrificed.     

Forecasting Irregularly Spaced UHF Financial Data: Realized Volatility vs UHF-GARCH Models

A new literature has been recently devoted to the modeling of ultra-high-frequency (UHF) data. Our first aim is to develop an empirical application of UHF-GARCH models to forecast future volatilities on irregularly spaced data. We also compare the out-sample performance of these generalized autoregressive conditional heteroskedastic (GARCH) models with the realized volatility method. We propose a procedure to account for the time deformation problem and show how to use these models for computing daily Value at Risk (VaR).     

Cumulant instrument estimators for hedge fund return models with errors in variables

We revisit the factors incorporated in asset pricing models following the recent developments in financial markets – i.e., the rise of shadow banking and the change in the transmission channel of monetary policy. We propose two versions of the Fung and Hsieh (2004) hedge fund return model, especially an augmented market model which accounts for the new dynamics of financial markets and the procyclicality of hedge fund returns. We run these models with an innovative Hausman procedure, tackling the measurement errors embedded in the models factor loadings. Our empirical method also allows for confronting the drawbacks of the instruments used to estimate hedge fund asset pricing models.     

Modelling conditional moments and correlation with the continuous hidden-threshold-skew-normal distribution

A key issue in modelling conditional densities of returns of financial assets is the time-variation of conditional volatility. The classic econometric approach models volatility of returns with the generalized autoregressive conditional heteroscedasticity (GARCH) models where the conditional mean and the conditional volatility depend only on historical prices. We propose a new family of distributions in which the conditional distribution depends on a latent continuous factor with a continuum of states. The distribution has an interpretation in terms of a mixture distribution with time-varying mixing probabilities. The distribution parameters have economic interpretations in terms of conditional volatilities and correlations of the returns with the hidden continuous state. We show empirically that this distribution outperforms its main competitor, the mixed normal conditional distribution, in terms of capturing the stylized facts known for stock returns, namely, volatility clustering, leverage effect, skewness, kurtosis and regime dependence.     

Efectos de las remesas de migrantes mexicanos en el Canadá en las explotaciones agrarias mexicanas

Con datos de una encuesta a participantes en el Programa de Trabajadores Agrícolas Temporales México‐Canadá, los autores estiman un modelo de ecuaciones simultáneas de mínimos cuadrados ordinarios y encuentran que las remesas impulsan las inversiones agrícolas en México, que a su vez incrementan los ingresos agrícolas. También observan una influencia positiva de las remesas en los ingresos no agrícolas en México, ya que permiten a los encuestados emprender y diversificar sus inversiones. Ello refrenda la teoría de la «nueva economía de la migración laboral», según la cual las remesas contribuyen al desarrollo económico al compensar la falta de créditos en la función de inversión de las explotaciones agrarias familiares.     

El trabajo y las normas internacionales de contabilidad. Una cuestión de justicia social

Como garante internacional de la justicia social, la OIT se enfrenta a una revolución contable que ha culminado con la formulación de las Normas Internacionales de Contabilidad (NIC-NIIF). Antiguamente, la contabilidad medía la economía en relación con las capacidades y responsabilidades de los trabajadores y de sus empleadores. Hoy las NIC-NIIF han perdido el sentido de la medida del trabajo y de la empresa al tomar esta como una entidad cibernética capaz de reorganizarse indefinidamente a costa de infinitas desigualdades. El autor señala las incoherencias de este modelo y demuestra la necesidad de restituir el valor contable del trabajo.     

IPO Pricing and Share Allocation: The Importance of Being Ignorant

Since an underwriter sets an IPO's offer price without knowing its market value, investors can acquire information about its value and avoid overpriced deals (“lemon‐dodge”). To mitigate this well‐known risk, the bank enters into a repeat game with a coalition of investors who do not lemon‐dodge in exchange for on‐average underpriced shares. We (i) derive and test a quantitative IPO pricing rule (showing that tech IPOs were not excessively underpriced during the boom of the 1990s); and (ii) analyzing a unique multibank data set, find strong support for the conjecture that a bank preferentially allocates shares to its coalition.