全球智库信息集成服务系统(G2TT): DP8828 U-MIDAS: MIDAS regressions with unrestricted lag polynomials

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来源类型	Discussion paper
规范类型	论文
来源ID	DP8828
	DP8828 U-MIDAS: MIDAS regressions with unrestricted lag polynomials
	Christian Schumacher; Massimiliano Marcellino; Claudia Foroni
发表日期	2012-02-01
出版年	2012
语种	英语
摘要	Mixed-data sampling (MIDAS) regressions allow to estimate dynamic equations that explain a low-frequency variable by high-frequency variables and their lags. When the difference in sampling frequencies between the regressand and the regressors is large, distributed lag functions are typically employed to model dynamics avoiding parameter proliferation. In macroeconomic applications, however, differences in sampling frequencies are often small. In such a case, it might not be necessary to employ distributed lag functions. In this paper, we discuss the pros and cons of unrestricted lag polynomials in MIDAS regressions. We derive unrestricted MIDAS regressions (U-MIDAS) from linear high-frequency models, discuss identification issues, and show that their parameters can be estimated by OLS. In Monte Carlo experiments, we compare U-MIDAS to MIDAS with functional distributed lags estimated by NLS. We show that U-MIDAS performs better than MIDAS for small differences in sampling frequencies. On the other hand, with large differing sampling frequencies, distributed lag-functions outperform unrestricted polynomials. The good performance of U-MIDAS for small differences in frequency is confirmed in an empirical application on nowcasting Euro area and US GDP using monthly indicators.
主题	International Macroeconomics
关键词	Distributed lag polynomals Mixed data sampling Nowcasting Time aggregation
URL	https://cepr.org/publications/dp8828
来源智库	Centre for Economic Policy Research (United Kingdom)
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/537664
推荐引用方式 GB/T 7714	Christian Schumacher,Massimiliano Marcellino,Claudia Foroni. DP8828 U-MIDAS: MIDAS regressions with unrestricted lag polynomials. 2012.