Bayesian binary quantile regression for the analysis of Bachelor-Master transition

The multi-cycle organization of modern university systems stimulates the interest in studying the progression to higher level degree courses during the academic career. In particular, after the achievement of the first level qualification (Bachelor degree), students have to decide whether to continue their university studies, by enrolling in a second level (Master) programme, or to conclude their training experience. In this work we propose a binary quantile regression approach to analyze the Bachelor-Master transition phenomenon with the adoption of the Bayesian inferential perspective. In addition to the traditional predictors of academic outcomes, such as the personal characteristics and the field of study, different aspects of the student's performance are considered. Moreover, a new contextual variable, indicating the type of university regulations, is taken into account in the model specification. The utility of the Bayesian binary quantile regression to characterize the non-continuation decision after the first cycle studies is illustrated with an application to administrative data of Bachelor graduates at the School of Economics of Sapienza University of Rome and compared with a more conventional logistic regression approach.Comment: 24 pages, 7 figures and 3 table

Optimal Monetary Policy with Durable Consumption Goods and Factor Demand Linkages

This paper deals with the implications of factor demand linkages for monetary policy design. We develop a dynamic general equilibrium model with two sectors that produce durable and non-durable goods, respectively. Part of the output produced in each sector is used as an intermediate input of production in both sectors, according to an input-output matrix calibrated on the US economy. As shown in a number of recent contributions, this roundabout technology allows us to reconcile standard two-sector New Keynesian models with the empirical evidence showing co-movement between durable and non-durable spending in response to a monetary policy shock. A main result of our monetary policy analysis is that strategic complementarities generated by factor demand linkages amplify social welfare loss. As the degree of interconnection between sectors increases, the cost of misperceiving the correct production technology of each sector can rise substantially. In addition, the transmission of different sources of exogenous perturbation is altered, compared to what is commonly observed in standard two-sector models without factor demand linkages. In this respect, the role of the relative price of non-durable goods is crucial, as this does not only influence the user cost of durables through the conventional demand channel, but also affects in opposite directions the real marginal cost of production in either sector through the intermediate input channel.input-output interactions, durable goods, optimal monetary policy

Speculation in the oil market

The run-up in oil prices after 2004 coincided with a growing flow of investment to commodity markets and an increased price comovement between different commodities. We analyze whether speculation in the oil market played a key role in driving this salient empirical pattern. We identify oil shocks from a large dataset using a factor-augmented autoregressive (FAVAR) model. We analyze the role of speculation in comparison to supply and demand forces as drivers of oil prices. The main results are as follows: (i) While global demand shocks account for the largest share of oil price fluctuations, financial speculative demand shocks are the second most important driver. (ii) The comovement between oil prices and the price of other commodities is explained by global demand and financial speculative demand shocks. (iii) The increase in oil prices in the last decade is mainly explained by the strength of global demand. However, financial speculation played a significant role in the oil price increase between 2004 and 2008, and its subsequent collapse. Our results support the view that the financialization process of commodity markets explains part of the recent increase in oil prices.Petroleum products - Prices ; Vector autoregression ; Speculation

On the Lp-quantiles for the Student t distribution

L_p-quantiles represent an important class of generalised quantiles and are defined as the minimisers of an expected asymmetric power function, see Chen (1996). For p=1 and p=2 they correspond respectively to the quantiles and the expectiles. In his paper Koenker (1993) showed that the tau quantile and the tau expectile coincide for every tau in (0,1) for a class of rescaled Student t distributions with two degrees of freedom. Here, we extend this result proving that for the Student t distribution with p degrees of freedom, the tau quantile and the tau L_p-quantile coincide for every tau in (0,1) and the same holds for any affine transformation. Furthermore, we investigate the properties of L_p-quantiles and provide recursive equations for the truncated moments of the Student t distribution

Large deviations for risk measures in finite mixture models

Due to their heterogeneity, insurance risks can be properly described as a mixture of different fixed models, where the weights assigned to each model may be estimated empirically from a sample of available data. If a risk measure is evaluated on the estimated mixture instead of the (unknown) true one, then it is important to investigate the committed error. In this paper we study the asymptotic behaviour of estimated risk measures, as the data sample size tends to infinity, in the fashion of large deviations. We obtain large deviation results by applying the contraction principle, and the rate functions are given by a suitable variational formula; explicit expressions are available for mixtures of two models. Finally, our results are applied to the most common risk measures, namely the quantiles, the Expected Shortfall and the shortfall risk measures

How does market architecture affect price dynamics ? A time series analysis of the Italian day-ahead electricity prices

How do changes in the market architecture affect the dynamics of deregulated electricity prices? We investigate this issue in the context of the Italian Power Exchange (IPEX), using data on the daily average day-ahead price (PUN) between April 2004 and December 2008. Estimates of baseline time series models (ARMAX and ARMAX-EGARCH) and their forecasting performances suggest that the trend in natural gas prices, deterministic weekly patterns, the impact of perceived temperatures, persistence in conditional volatility and the inverse leverage effect are essential features of the PUN dynamics. We then augment the best-performing models with dummies that account for changes in the market architecture, such as the introduction of contracts for differences (CfDs) to support renewables, trading of white certificates for energy efficiency, and the demandside liberalization. The findings show that changes in the market architecture have only affected the PUN volatility. Specifically, CfDs have mitigated volatility, while white certificates and demand liberalization have increased it. Moreover, after controlling for reforms the inverse leverage effect vanishes, and the persistence in volatility is lower than in the baseline estimates.electricity prices, Italian power exchange, market architecture, ARMA, EGARCH

Optimal Monetary Policy with Durable Consumption Goods and Factor Demand Linkages

This paper deals with the implications of factor demand linkages for monetary policy design. We consider a dynamic general equilibrium model with two sectors that produce durable and non-durable goods, respectively. Part of the output of each sector serves as a production input in both sectors, in accordance with a realistic input-output structure. Strategic complementarities induced by factor demand linkages significantly alter the transmission of exogenous shocks and amplify the loss of social welfare under optimal monetary policy, compared to what is observed in standard two-sector models. The distinction between value added and gross output that naturally arises in this context is of key importance to explore the welfare properties of the model economy. A flexible inflation targeting regime is close to optimal only if the central bank balances inflation and value added variability. Otherwise, targeting gross output variability entails a substantial increase in the loss of welfare.Input-Output Interactions, Durable Goods, Optimal Monetary Policy

Factor demand linkages, technology shocks and the business cycle

This paper argues that factor demand linkages can be important for the transmission of both sectoral and aggregate shocks. We show this using a panel of highly disaggregated manufacturing sectors together with sectoral structural VARs. When sectoral interactions are explicitly accounted for, a contemporaneous technology shock to all manufacturing sectors implies a positive response in both output and hours at the aggregate level. Otherwise there is a negative correlation, as in much of the existing literature. Furthermore, we find that technology shocks are important drivers of business cycle.