Ita-Coin: A New Coincident Indicator for the Italian Economy

Aprigliano, Valentina; Bencivelli, Lorenzo

doi:10.2139/ssrn.2405416

Cited by 26 publications

(4 citation statements)

References 116 publications

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“…LASSO regression was introduced by Tibshirani (1996) as a new method of estimation, in linear models, that minimizes the residual sum of the squares (RSS) subject to the sum of the absolute value of the coefficients being less than a constant. In macroeconomic applications, Aprigliano and Bencivelli (2013) use the LASSO regression to select the relevant economic and financial variables in a large data set with the goal of estimating a new Italian coincident indicator.…”

Section: Methodsmentioning

confidence: 99%

Timely Estimates of the Monthly Mexican Economic Activity

Corona

González–Farías

López-Pérez

2022

Journal of Official Statistics

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In this article, we present a new approach based on dynamic factor models (DFMs) to perform accurate nowcasts for the percentage annual variation of the Mexican Global Economic Activity Indicator (IGAE), the commonly used variable as an approximation of monthly GDP. The procedure exploits the contemporaneous relationship of the timely traditional macroeconomic time series and nontraditional variables as Google Trends with respect to the IGAE. We evaluate the performance of the approach in a pseudo real-time framework, which includes the pandemic of COVID-19, and conclude that the procedure obtains accurate estimates, for one and two-steps ahead, above all, given the use of Google Trends. Another contribution for economic nowcasting is that the approach allows to disentangle the key variables in the DFM by estimating the confidence interval for the factor loadings, hence allows to evaluate the statistical significance of the variables in the DFM. This approach is used in official statistics to obtain preliminary and accurate estimates for IGAE up to 40 days before the official data release.

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Section: Methodsmentioning

confidence: 99%

Timely Estimates of the Monthly Mexican Economic Activity

Corona

González–Farías

López-Pérez

2022

Journal of Official Statistics

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“…In macroeconomic applications, Aprigliano and Bencivelli (2013) use LASSO regression to select the relevant economic and financial variables in a large data set with the goal of estimating a new Italian coincident indicator.…”

Section: Lasso Regressionmentioning

confidence: 99%

A nowcasting approach to generate timely estimates of Mexican economic activity: An application to the period of COVID-19

Corona,

González-Farías,

López-Pérez

2021

Preprint

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In this paper, we present a new approach based on dynamic factor models (DFMs) to perform nowcasts for the percentage annual variation of the Mexican Global Economic Activity Indicator (IGAE in Spanish). The procedure consists of the following steps: i) build a timely and correlated database by using economic and financial time series and realtime variables such as social mobility and significant topics extracted by Google Trends; ii) estimate the common factors using the two-step methodology of Doz et al. (2011); iii) use the common factors in univariate time-series models for test data; and iv) according to the best results obtained in the previous step, combine the statistically equal better nowcasts (Diebold-Mariano test) to generate the current nowcasts. We obtain timely and accurate nowcasts for the IGAE, including those for the current phase of drastic drops in the economy related to COVID-19 sanitary measures. Additionally, the approach allows us to disentangle the key variables in the DFM by estimating the confidence interval for both the factor loadings and the factor estimates. This approach can be used in official statistics to obtain preliminary estimates for IGAE up to 50 days before the official results.

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“…As a result, if used in conjunction with appropriate econometric techniques, they can provide significant benefit to policymakers who-for instance, in the most recent period due to the ongoing pandemic-need timely nowcasts of the economic cycle to immediately assess the extent of the recession, adopt timely economic policy measures and monitor the intensity and speed of the recovery. 2 Traditional business cycle/coincident indicators are based on the observation of real economic activity variables sampled at a quarterly or a monthly frequency (Altissimo et al, 2010;Aprigliano & Bencivelli, 2013;Frale et al, 2011;Marcellino et al, 2016;Bencivelli et al, 2017), 3 with the addition of a few financial variables (e.g., the slope of the yield curve and a broad equity index). Despite this, the interest in using higher frequency data for tracking economic developments is not novel.…”

Section: Introductionmentioning

confidence: 99%

“…Traditional business cycle/coincident indicators are based on the observation of real economic activity variables sampled at a quarterly or a monthly frequency (Altissimo et al, 2010; Aprigliano & Bencivelli, 2013; Frale et al, 2011; Marcellino et al, 2016; Bencivelli et al, 2017), 3 with the addition of a few financial variables (e.g., the slope of the yield curve and a broad equity index). Despite this, the interest in using higher frequency data for tracking economic developments is not novel.…”

Section: Introductionmentioning

confidence: 99%

Nowcasting the state of the Italian economy: The role of financial markets

Ceci

Silvestrini

2023

Journal of Forecasting

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This paper compares several methods for constructing weekly nowcasts of recession probabilities in Italy, with a focus on the most recent period of the Covid‐19 pandemic. The common thread of these methods is that they use, in different ways, the information content provided by financial market data. In particular, a battery of probit models are estimated after extracting information from a large dataset of more than 130 financial market variables observed at a weekly frequency. The accuracy of these models is explored in a pseudo out‐of‐sample nowcasting exercise. The results demonstrate that nowcasts derived from probit models estimated on a large set of financial variables are, on average, more accurate than those delivered by standard probit models estimated on a single financial covariate, such as the slope of the yield curve. The proposed approach performs well even compared with probit models estimated on single time series of real economic activity variables, such as industrial production, business tendency survey data or composite PMI indicators. Overall, the financial indicators used in this paper can be easily updated as soon as new data become available on a weekly basis, thus providing reliable early estimates of the Italian business cycle.

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Ita-Coin: A New Coincident Indicator for the Italian Economy

Cited by 26 publications

References 116 publications

Timely Estimates of the Monthly Mexican Economic Activity

Timely Estimates of the Monthly Mexican Economic Activity

A nowcasting approach to generate timely estimates of Mexican economic activity: An application to the period of COVID-19

Nowcasting the state of the Italian economy: The role of financial markets

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