A comparison between VAR processes jointly modeling GDP and Unemployment rate in France and Germany

Iorio, Francesca Di; Triacca, Umberto

doi:10.1007/s10260-021-00594-2

Cited by 6 publications

(3 citation statements)

References 27 publications

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“…Francesca Di Iorio and Umberto Triacca used a vector autoregressive model (VAR) to jointly model the growth rates of both GDP and unemployment [4].…”

Section: Literature Reviewmentioning

confidence: 99%

The Research and Forecasts on Real GDP Growth and the Unemployment Rate in the United States

Zhong

2024

HBEM

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Empirically, the real GDP growth rates and the unemployment rates are typically negatively correlated. From the post-COVID-19 era, countries around the world have not fully recovered from the pandemic. In this case, forecasts of GDP growth and unemployment rate are a vital reference for governments to recover economies in the future. This study collected the real GDP and unemployment rate data of the United States from 1948 to 2023, studied their relationship through linear and nonlinear regression, and predicted their future trends, respectively, with the ARIMA model. By comparing linear regression and nonlinear regression (locally estimated scatterplot smoothing) between the GDP growth rate and change in the unemployment rate, this study found that nonlinear regression can more accurately express the relationship between these two factors. The forecasts of GDP growth rates and unemployment rates provided by the ARIMA model show a relatively optimistic future with healthy GDP growth and low unemployment. However, wide ranges of confidence intervals also pointed to the danger of low GDP growth and widespread unemployment. The relationship between GDP and unemployment and their projections in this study serve as valuable references for future economic planning and incentive policies in the U.S. government. It may also be applicable to other countries that have similar economic conditions.

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“…Francesca Di Iorio and Umberto Triacca used a vector autoregressive model (VAR) to jointly model the growth rates of both GDP and unemployment [4].…”

Section: Literature Reviewmentioning

confidence: 99%

The Research and Forecasts on Real GDP Growth and the Unemployment Rate in the United States

Zhong

2024

HBEM

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“…Abonazel et al [2] used ARIMA model to predict Egyptian GDP in next decade from 2019, and Salisu et al [99] analysed how the oil uncertainty stock affect 33 countries' GDP and the influence between the countries using a global VAR. Iorio et al [55] compared France and Germany 's unemployment rate and GDP growth rate in the future basic on a VAR model. ARIMA and VAR models remain widely applied in a range of econometrics and finance applications [52,29].…”

Section: Literature Reviewmentioning

confidence: 99%

Recursive deep learning framework for forecasting the decadal world economic outlook

Wang¹,

Beard²,

Hawkins³

et al. 2023

Preprint

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Gross domestic product (GDP) is the most widely used indicator in macroeconomics and the main tool for measuring a country's economic ouput. Due to the diversity and complexity of the world economy, a wide range of models have been used, but there are challenges in making decadal GDP forecasts given unexpected changes such as pandemics and wars. Deep learning models are well suited for modeling temporal sequences have been applied for time series forecasting. In this paper, we develop a deep learning framework to forecast the GDP growth rate of the world economy over a decade. We use Penn World Table as the source of our data, taking data from 1980 to 2019, across 13 countries, such as Australia, China, India, the United States and so on. We test multiple deep learning models, LSTM, BD-LSTM, ED-LSTM and CNN, and compared their results with the traditional time series model (ARIMA,VAR). Our results indicate that ED-LSTM is the best performing model. We present a recursive deep learning framework to predict the GDP growth rate in the next ten years. We predict that most countries will experience economic growth slowdown, stagnation or even recession within five years; only China, France and India are predicted to experience stable, or increasing, GDP growth.

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“…A degree of economic convergence between European economies is needed for a well-functioning monetary union. If there are large differences between countries, achieving common goals is more difficult (Iorio & Triacca, 2022).…”

Section: Literature Reviewmentioning

confidence: 99%

Unemployment Rate and GDP Growth Rate in Selected European Countries

Živković¹

2022

Balkans JETSS

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GDP growth rate and unemployment rate are two crucial macroeconomic variables - their correlation is an important indicator for policymakers and it has been frequently analyzed. This research aims to analyze the GDP growth rate and unemployment rate in EU founders, Visegrad group, and Western Balkan countries and to determine if the negative correlation between these variables exists, to point to differences between developed and developing countries, and to indicate real convergence of developing countries towards developed ones. Data is analyzed on a quarterly level from Q1 2010 to Q4 2021 and the methodology of this paper consists of empirical data analysis, descriptive statistics, and panel analysis for each country group. Obtained results point to a negative correlation in all 3 country groups, but it is statistically significant only in EU founders countries, and the convergence of the Visegrad group and Western Balkan countries towards developed ones can be acknowledged.

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A comparison between VAR processes jointly modeling GDP and Unemployment rate in France and Germany

Cited by 6 publications

References 27 publications

The Research and Forecasts on Real GDP Growth and the Unemployment Rate in the United States

The Research and Forecasts on Real GDP Growth and the Unemployment Rate in the United States

Recursive deep learning framework for forecasting the decadal world economic outlook

Unemployment Rate and GDP Growth Rate in Selected European Countries

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