{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T13:27:29Z","timestamp":1765546049751},"reference-count":46,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2015,11,9]],"date-time":"2015-11-09T00:00:00Z","timestamp":1447027200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J of Applied Econometrics"],"published-print":{"date-parts":[[2016,11]]},"abstract":"<jats:title>Summary<\/jats:title><jats:p>In this paper, we propose a time\u2010varying parameter vector autoregression (VAR) model with stochastic volatility which allows for estimation on data sampled at different frequencies. Our contribution is twofold. First, we extend the methodology developed by Cogley and Sargent (Drifts and volatilities: monetary policies and outcomes in the post WWII U.S.<jats:italic>Review of Economic Studies<\/jats:italic>2005;<jats:bold>8<\/jats:bold>: 262\u2013302) and Primiceri (Time varying structural vector autoregressions and monetary policy.<jats:italic>Review of Economic Studies<\/jats:italic>2005;<jats:bold>72<\/jats:bold>: 821\u2013852) to a mixed\u2010frequency setting. In particular, our approach allows for the inclusion of two different categories of variables (high\u2010frequency and low\u2010frequency) into the same time\u2010varying model. Second, we use this model to study the macroeconomic effects of government spending shocks in Italy over the 1988:Q4\u20132013:Q3 period. Italy\u2014as well as most other euro area economies\u2014is characterized by short quarterly time series for fiscal variables, whereas annual data are generally available for a longer sample before 1999. Our results show that the proposed time\u2010varying mixed\u2010frequency model improves on the performance of a simple linear interpolation model in generating the true path of the missing observations. Second, our empirical analysis suggests that government spending shocks tend to have positive effects on output in Italy. The fiscal multiplier, which is maximized at the 1\u2010year horizon, follows a U\u2010shape over the sample considered: it peaks at around 1.5 at the beginning of the sample; it then stabilizes between 0.8 and 0.9 from the mid 1990s to the late 2000s, before rising again to above unity during the recent crisis. Copyright \u00a9 2015 John Wiley &amp; Sons, Ltd.<\/jats:p>","DOI":"10.1002\/jae.2489","type":"journal-article","created":{"date-parts":[[2015,11,9]],"date-time":"2015-11-09T09:20:46Z","timestamp":1447060846000},"page":"1276-1290","source":"Crossref","is-referenced-by-count":18,"title":["Combining Time Variation and Mixed Frequencies: an Analysis of Government Spending Multipliers in Italy"],"prefix":"10.1002","volume":"31","author":[{"given":"Jacopo","family":"Cimadomo","sequence":"first","affiliation":[{"name":"European Central Bank, Frankfurt am Main Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Antonello","family":"D'Agostino","sequence":"additional","affiliation":[{"name":"European Stability Mechanism Luxembourg"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2015,11,9]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordhb\/9780195398649.013.0009"},{"key":"e_1_2_6_3_1","doi-asserted-by":"crossref","unstructured":"AsimakopoulosS ParedesJ WarmedingerT.2013.Forecasting Fiscal time series using mixed frequency data. 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