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Author:Luciani, Matteo 

Working Paper
Common Factors, Trends, and Cycles in Large Datasets

This paper considers a non-stationary dynamic factor model for large datasets to disentangle long-run from short-run co-movements. We first propose a new Quasi Maximum Likelihood estimator of the model based on the Kalman Smoother and the Expectation Maximisation algorithm. The asymptotic properties of the estimator are discussed. Then, we show how to separate trends and cycles in the factors by mean of eigenanalysis of the estimated non-stationary factors. Finally, we employ our methodology on a panel of US quarterly macroeconomic indicators to estimate aggregate real output, or Gross ...
Finance and Economics Discussion Series , Paper 2017-111

Working Paper
Nowcasting Indonesia

We produce predictions of the current state of the Indonesian economy by estimating a dynamic factor model on a dataset of eleven indicators (also followed closely by market operators) over the time period 2002 to 2014. Besides the standard difficulties associated with constructing timely indicators of current economic conditions, Indonesia presents additional challenges typical to emerging market economies where data are often scant and unreliable. By means of a pseudo-real-time forecasting exercise we show that our model outperforms univariate benchmarks, and it does comparably with ...
Finance and Economics Discussion Series , Paper 2015-100

Working Paper
Common and Idiosyncratic Inflation

We use a dynamic factor model to disentangle changes in prices due to economy-wide (common) shocks, from changes in prices due to idiosyncratic shocks. Using 146 disaggregated individual price series from the U.S. PCE price index, we find that most of the fluctuations in core PCE prices observed since 2010 have been idiosyncratic in nature. Moreover, we find that common core inflation responds to economic slack, while the idiosyncratic component does not. That said, even after filtering out idiosyncratic factors, the estimated Phillips curve is extremely flat post-1995. Therefore, our ...
Finance and Economics Discussion Series , Paper 2020-024

Discussion Paper
Do National Account Statistics Underestimate US Real Output Growth?

In this note, we introduce a new estimate of GDO obtained from a Non-Stationary Dynamic Factor model estimated on a large dataset of US macroeconomic indicators.
FEDS Notes , Paper 2018-01-09-1

Working Paper
Non-Stationary Dynamic Factor Models for Large Datasets

We study a Large-Dimensional Non-Stationary Dynamic Factor Model where (1) the factors Ft are I (1) and singular, that is Ft has dimension r and is driven by q dynamic shocks with q less than r, (2) the idiosyncratic components are either I (0) or I (1). Under these assumption the factors Ft are cointegrated and modeled by a singular Error Correction Model. We provide conditions for consistent estimation, as both the cross-sectional size n, and the time dimension T, go to infinity, of the factors, the loadings, the shocks, the ECM coefficients and therefore the Impulse Response Functions. ...
Finance and Economics Discussion Series , Paper 2016-024

Discussion Paper
Quantifying the COVID-19 Effects on Core PCE Price Inflation

The 12-month change in core PCE price inflation was 1.5 percent in December. Why was core inflation so low in 2020? How much of this weakness can be attributed to the COVID pandemic? And what does this mean for inflation going forward?
FEDS Notes , Paper 2021-02-25

Working Paper
Dynamic Factor Models, Cointegration, and Error Correction Mechanisms

The paper studies Non-Stationary Dynamic Factor Models such that: (1) the factors Ft are I(1) and singular, i.e. Ft has dimension r and is driven by a q-dimensional white noise, the common shocks, with q < r, and (2) the idiosyncratic components are I(1). We show that Ft is driven by r-c permanent shocks, where c is the cointegration rank of Ft, and q - (r - c) < c transitory shocks, thus the same result as in the non-singular case for the permanent shocks but not for the transitory shocks. Our main result is obtained by combining the classic Granger Representation Theorem with recent ...
Finance and Economics Discussion Series , Paper 2016-018

Working Paper
Oil Price Pass-Through into Core Inflation

We estimate the oil price pass-through into consumer prices both in the US and in the euro area. In particular, we disentangle the specific effect that an oil price change might have on each disaggregate price, from the effect on all prices that an oil price change might have since it affects the whole economy. To do so, we first estimate a Dynamic Factor Model on a panel of disaggregate price indicators, and then we use VAR techniques to estimate the pass-through. Our results show that the oil price passes through core inflation only via its effect on the whole economy. This pass-through is ...
Finance and Economics Discussion Series , Paper 2017-085

Discussion Paper
Comparing Two Measures of Core Inflation: PCE Excluding Food & Energy vs. the Trimmed Mean PCE Index

The goal of this note is to provide an assessment of two of the most commonly used indicators of core inflation: the PCE price index excluding food and energy (an exclusion index), and the Dallas Fed trimmed mean PCE price index (a central-tendency statistical measure).
FEDS Notes , Paper 2019-08-02-1

Discussion Paper
Oil Price Pass-Through into Core Inflation

Quantifying the magnitude and establishing the timing of the pass-through of oil price changes to consumer prices is crucial for forecasting inflation. Characterizing this pass-through is particularly important because oil prices tend to undergo wide fluctuations. In this note we presented estimates of the oil price pass-through into consumer prices both in the US and in the euro area.
FEDS Notes , Paper 2017-10-19-1

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