Papers by Andrea Silvestrini
The Annals of Applied Statistics
We propose a regression discontinuity design which can be employed when assignment to treatment i... more We propose a regression discontinuity design which can be employed when assignment to treatment is determined by an ordinal variable. The proposal first requires estimating an ordered probit model for the ordinal running variable. The estimated probability of being assigned to treatment is then adopted as a latent continuous running variable and used to identify a covariate-balanced subsample around the threshold. Assuming local unconfoundedness of the treatment in the subsample, an estimate of the effect of the program is obtained by employing a weighted estimator of the average treatment effect. Three types of balancing weightsoverlap weights, inverse probability weights and ATT weights-are considered. An empirical M-estimator for the variance of the weighting estimator is derived. We apply the method to evaluate the causal effect of the Corporate Sector Purchase Programme of the European Central Bank on bond spreads.
SSRN Electronic Journal, 2020
The causal effect of the European Central Bank's corporate bond purchase program on bond spreads ... more The causal effect of the European Central Bank's corporate bond purchase program on bond spreads in the primary market is evaluated, making use of a novel regression discontinuity design. The results indicate that the program did not, on average, permanently alter the yield spreads of eligible bonds relative to those of noneligible. Combined with evidence from previous studies, this finding suggests the effects of central bank asset purchase programs are in no way limited to the prices of the specific assets acquired.
SSRN Electronic Journal, 2016
We analyse the developments of investment and investment financing in Italy since 1995, based on ... more We analyse the developments of investment and investment financing in Italy since 1995, based on data from national accounts and the flow of funds. The exceptional fall in investment after the global financial crisis in 2007 concerned all institutional sectors and asset categories. However, appropriately deflated data highlight the more intense fall of household capital expenditure. Consistently, on the asset side, construction was one of the most hard-hit capital goods; ICT and intangible investment instead weathered the double recession better. Focusing on investment financing, the eruption of the crisis caused a major contraction in the availability of external finance for non-financial corporations and households. Long-term loans to non-financial corporations became more important, crowding out their short-term counterparts. Also the weight of debt securities increased significantly, especially after 2008.
SSRN Electronic Journal, 2018
Using significantly under-exploited data from institutional sector accounts, we assess the main d... more Using significantly under-exploited data from institutional sector accounts, we assess the main drivers of both firms' and households' investment in Italy over the past two decades. We estimate a vector error correction model separately for firms and for households. Our findings support the existence in both institutional sectors of a long-run equilibrium relationship between investment, income and the user cost of capital, as predicted by the flexible neoclassical model, as well as adjustment dynamics towards the equilibrium level. Moreover, we find evidence that an increase in uncertainty and a decline in economic sentiment have a dampening effect on investment. Furthermore, high indebtedness, measured by financial accounts data, and tight credit constraints, based on survey data for firms, are found to have significantly hindered both firms' and households' capital accumulation, again in the short run. This leads us to conclude that studies that disregard the role of debt or financing constraints are unable to fully explain investment dynamics in Italy, especially in the most recent years of sharp contraction.
Statistical Methods & Applications, 2019
In this paper we examine the empirical features of both the business and financial cycles in Ital... more In this paper we examine the empirical features of both the business and financial cycles in Italy. We employ univariate and multivariate trend-cycle decompositions based on unobserved component models. Univariate estimates highlight the different cyclical properties (persistence, duration and amplitude) of real GDP and real credit to the private sector. Multivariate estimates uncover the presence of feedback effects between the real and financial cycles. At the same time, in the most recent period (2015-2016), the multivariate approach highlights a wider output gap than that estimated by the univariate models considered in this paper.
The working paper series promotes the dissemination of economic research produced in the Departme... more The working paper series promotes the dissemination of economic research produced in the Department of the Treasury (DT) of the Italian Ministry of Economy and Finance (MEF) or presented by external economists on the occasion of seminars organized by MEF on topics of institutional interest to the DT, with the aim of stimulating comments and suggestions. The views expressed in the working papers are those of the authors and do not necessarily reflect those of the MEF and the DT.
SSRN Electronic Journal, 2015
We examine the inter-linkages between financial factors and real economic activity. We review the... more We examine the inter-linkages between financial factors and real economic activity. We review the main theoretical approaches that allow financial frictions to be embedded into general equilibrium models. We outline, from a policy perspective, the most recent empirical papers focusing on the propagation of exogenous shocks to the economy, with a particular emphasis on works dealing with time variation of parameters and other types of nonlinearities. We then present an application to the analysis of the changing transmission of financial shocks in the euro area. Results show that the effects of a financial shock are time-varying and contingent on the state of the economy. They are of negligible importance in normal times but they greatly matter in conditions of stress.
This paper presents and evaluates a new approach to forecasting annual budget deficits using mont... more This paper presents and evaluates a new approach to forecasting annual budget deficits using monthly data for an EU country. It aims at improving the accuracy of deficit forecasts, a relevant issue to policy makers in the Eurozone, and at proposing a replicable methodology exploiting public quantitative information on budgetary data. Using French data on central government revenues and expenditures, the method we propose consists of: 1) estimating monthly ARIM A models for all items of central government revenues and expenditures; 2) inferring the annual ARIM A models from the monthly models; 3) using the inferred annual ARIM A models to perform one-step-ahead forecasts for each item; 4) compounding the annual forecasts of all revenues and expenditures to obtain an annual budget deficit forecast. The major empirical benefit of this technique is that as soon as new monthly data becomes available, annual deficit forecasts are updated. This allows us to detect in advance possible slippages in central government finances. For years 2002, 2003 and 2004, forecasts obtained following the proposed approach are compared with a benchmarking method and with official predictions published by the French government. An evaluation of their relative performance is provided.
In this paper we present new estimates of the effect of household financial and real wealth on co... more In this paper we present new estimates of the effect of household financial and real wealth on consumption. The analysis refers to eleven OECD countries and takes into account the years from 1997 to 2008. Unlike most of the previous literature, we exploit European quarterly harmonized data on household financial assets and liabilities, which have been taken from the flow of funds. We measure not only the effect of total financial wealth on consumption, but we also consider the impact of a subset of those financial assets (i.e., quoted shares, mutual funds, insurance technical reserves) that are more linked to the Stock Exchange. Furthermore, we implement a recent econometric approach that allows for more flexible assumptions in the non-stationary panel framework under consideration. Our main results show that both net financial and real wealth have a positive effect on consumption. Overall, the influence of net financial assets is stronger than that of real assets. Using quoted shar...
This paper compares the performance of "aggregate" and "disaggregate" predictors in forecasting c... more This paper compares the performance of "aggregate" and "disaggregate" predictors in forecasting contemporaneously aggregated vector ARMA processes. An aggregate predictor is built by forecasting directly the aggregate process, as it results from contemporaneous aggregation of the data generating vector process. A disaggregate predictor is obtained by aggregating univariate forecasts for the individual components of the data generating vector process. The necessary and sufficient condition for the equality of mean squared errors associated with the two competing methods is provided in the bivariate VMA(1) case. Furthermore, it is argued that the condition of equality of predictors as stated in is only sufficient (not necessary) for the equality of mean squared errors. Finally, it is shown that the equality of forecasting accuracy for the two predictors can be achieved using specific assumptions on the parameters of the VMA(1) structure. Monte Carlo simulations are in line with the analytical results. An empirical application that involves the problem of forecasting the Italian monetary aggregate M1 in the pre-EMU period is presented to illustrate the main findings.
In this paper we feature state-of-the-art econometric methodology of temporal aggregation for uni... more In this paper we feature state-of-the-art econometric methodology of temporal aggregation for univariate linear time series, namely ARIMA-GARCH models. We present a unified overview of temporal aggregation techniques for this broad class of processes and we explain in detail, although intuitively, the technical machinery behind the results. An empirical application with Belgian public deficit data illustrates the main issues.
Core Discussion Papers, 2005
In this paper we feature state-of-the-art econometric methodology of temporal aggregation for uni... more In this paper we feature state-of-the-art econometric methodology of temporal aggregation for univariate linear time series, namely ARIMA-GARCH models. We present a unified overview of temporal aggregation techniques for this broad class of processes and we explain in detail, although intuitively, the technical machinery behind the results. An empirical application with Belgian public deficit data illustrates the main issues.
The revision policy of seasonally adjusted balance sheet data in Italy
Http Dx Doi Org 10 1080 13504851 2011 560106, Apr 8, 2011
This article illustrates the seasonal adjustment procedure for bank deposits and loans in Italy f... more This article illustrates the seasonal adjustment procedure for bank deposits and loans in Italy focusing on the revision policy of seasonally adjusted data. Seasonal adjustment is conducted in a semi-automatic way, employing TRAMO–SEATS, one of the software packages most often used for the production of seasonally adjusted series. Regarding the frequency of data revisions, three alternative methods (current adjustment, concurrent adjustment and partial concurrent adjustment) are tested according to a quantitative criterion. An empirical application allows us to measure the speed of convergence of the estimates obtained with the aforementioned updating methods towards a ‘final’ value that can be considered a benchmark. The results suggest using the method of partial concurrent adjustment, which is based on the identification of the ARIMA model and of the deterministic components once a year, whereas the updating of the corresponding coefficients is undertaken every month.
Monitoring and forecasting annual public deficit every month: the case of France
Empir Econ, 2008
In this paper we forecast annual budget deficits using monthly information. Using French monthly ... more In this paper we forecast annual budget deficits using monthly information. Using French monthly data on central government revenues and expenditures, the method we propose consists of: (1) estimating monthly ARIMA models for all items of central government revenues and expenditures; (2) inferring the annual ARIMA models from the monthly models; (3) using the inferred annual ARIMA models to perform
Temporal aggregation of univariate time linear series models: a survey
Seasonal Adjustment of Bank Deposits and Loans
SSRN Electronic Journal, 2000
... 42 N u m e ro La destagionalizzazione dei depositi e dei prestiti bancari di Andrea Silvestri... more ... 42 N u m e ro La destagionalizzazione dei depositi e dei prestiti bancari di Andrea Silvestrini Page 2. Questioni di Economia e Finanza (Occasional papers) La destagionalizzazione dei depositi e dei prestiti bancari di Andrea Silvestrini Numero 42 Marzo 2009 Page 3. ...
We develop a methodology for using intra-annual data to forecast annual budget deficits. Our appr... more We develop a methodology for using intra-annual data to forecast annual budget deficits. Our approach aims at improving the accuracy of the deficit forecasts, a relevant issue to policy makers in the Eurozone and at proposing a replicable methodology using at best public quantitative information on budgetary data. Using French data on government (State) revenues and expenditures, we estimate intra-annual monthly ARIMA models for all the items of the central government revenues and expenditures. Next, applying temporal aggregation techniques, we infer parameters of the annual models from the estimated parameters of the intra-annual models. These parameters incorporate all the intra-annual information. Finally, we do one period ahead predictions. We are able to update the annual deficit forecast as soon as new monthly data are available. This allows us to detect possible slippages in central government finances.
The Italian financial cycle: 1861-2011
Cliometrica Journal of Historical Economics and Econometric History, 2014
ABSTRACT In this paper we investigate the main features of the Italian financial cycle, extracted... more ABSTRACT In this paper we investigate the main features of the Italian financial cycle, extracted by means of a structural trend-cycle decomposition of the credit-to-GDP ratio, using annual observations from 1861 to 2011. In order to draw conclusions based on solid historical data, we provide a thorough reconstruction of the key balance-sheet time series of Italian banks, considering all the main assets and liabilities over the last 150 years. We come to three main conclusions. First, while there was a close correlation between loans and deposits (relative to GDP) until the mid-1970s, over the last 30 years this link has become more tenuous, and the volume of loans has increased in relation to deposits. The banks have covered this “funding gap” mainly by issuing new debt securities. Second, the Italian financial cycle has a much longer duration than traditional business cycles. Third, taking into account the deviation of the credit-to-GDP ratio from its trend, an acceleration of credit preceded a banking crisis in 8 out of the 12 episodes listed by Reinhart and Rogoff (2009). A Logit regression confirms a positive association between the probability of a banking crisis and a previous acceleration of the credit-to-GDP gap. However, there were also periods - such as the early 1970s - in which the growth of the credit-to-GDP ratio was not followed by a banking crisis.
Short Term Inflation Forecasting: The M.E.T.A. Approach
SSRN Electronic Journal, 2000
Marginalization and aggregation of exponential smoothing models in forecasting portfolio volatility
Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2012
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Papers by Andrea Silvestrini