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Comparative Analysis of Different Univariate Forecasting Methods in Modelling and Predicting the Romanian Unemployment Rate for the Period 2021–2022
16 references·3 citing·41 second hop
Comparative Analysis of Different Univariate Forecasting Methods in Modelling and Predicting the Romanian Unemployment Rate for the Period 2021–2022 (2021)Comparative Analysis of Different Univari…Forecasting principles and practice (2018)Forecasting principles and pr…Growth and structural changes in employment in transition China (2009)Growth and structural changes…Towards a new early warning system of financial crises (2006)Towards a new early warning s…Forecasting the US unemployment rate (2003)Forecasting the US unemployme…MODELING ASYMMETRIES AND MOVING EQUILIBRIA IN UNEMPLOYMENT RATES (2002)MODELING ASYMMETRIES AND MOVI…Forecasting time series with sieve bootstrap (2002)Forecasting time series with …A state space framework for automatic forecasting using exponential smoothing methods (2002)A state space framework for a…Dynamic Asymmetries in U.S. Unemployment (1999)Dynamic Asymmetries in U.S. U…Forecasting Asymmetric Unemployment Rates (1998)Forecasting Asymmetric Unempl…Comparing Predictive Accuracy (1995)Comparing Predictive AccuracyComparing Predictive Accuracy (1994)Comparing Predictive AccuracyOn the limitations of comparing mean square forecast errors (1993)On the limitations of compari…Seasonal integration and cointegration (1990)Seasonal integration and coin…Forecasting with Univariate Box‐Jenkins Models (1983)Forecasting with Univariate B…Forecasting with Univariate Box - Jenkins Models : concepts and cases (1983)Forecasting with Univariate B…Book Review: Time Series Analysis: Forecasting and Control (1977)Book Review: Time Series Anal…Unemployment rate forecasting: LSTM-GRU hybrid approach (2023)Unemployment rate forecasting…Comparison of ARIMA, SutteARIMA, and Holt-Winters, and NNAR Models to Predict Food Grain in India (2023)Comparison of ARIMA, SutteARI…Unemployment Rates Forecasting with Grey-Based Models in the Post-COVID-19 Period: A Case Study from Vietnam (2021)Unemployment Rates Forecastin…Distribution of the Estimators for Autoregressive Time Series With a Unit Root (1979)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data (1993)Likelihood-Based Inference in Cointegrated Vector Autoregressive Models (1995)Automatic Time Series Forecasting: The forecast Package for R (2008)Statistical analysis of cointegration vectors (1988)MAXIMUM LIKELIHOOD ESTIMATION AND INFERENCE ON COINTEGRATION — WITH APPLICATIONS TO THE DEMAND FOR MONEY (1990)Another look at measures of forecast accuracy (2006)Exponential smoothing: The state of the art (1985)Forecasting methods and applications (1993)The M3-Competition: results, conclusions and implications (2000)Forecasting at Scale (2017)Testing for Serial Correlation in Least-Squares Regression When Some of the Regressors are Lagged Dependent Variables (1970)Forecasting Economic Time Series (2000)A simulation study of artificial neural networks for nonlinear time-series forecasting (2001)A fusion model of HMM, ANN and GA for stock market forecasting (2006)Support vector regression with genetic algorithms in forecasting tourism demand (2006)Specification Tests for the Multinomial Logit Model (1984)Currency crashes in emerging markets: An empirical treatment (1996)The Twin Crises: The Causes of Banking and Balance-of-Payments Problems (1999)Stories of the Twentieth Century for the Twenty-First (2011)Stories of the Twentieth Century for the Twenty-First (2012)Evaluating early warning indicators of banking crises: Satisfying policy requirements (2014)A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle (1989)Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation (1991)Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts (1998)A Comprehensive Look at The Empirical Performance of Equity Premium Prediction (2007)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)Combining forecasts: A review and annotated bibliography (1989)Testing the equality of prediction mean squared errors (1997)Consumption, Aggregate Wealth, and Expected Stock Returns (2001)Deep learning with long short-term memory networks for financial market predictions (2017)Applied Time Series Analysis for Managerial Forecasting. (1974)Learning the Innovation Journey: Order out of Chaos? (1996)Forecasting with artificial neural networks: (1998)Neural network forecasting for seasonal and trend time series (2003)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)Generalized autoregressive conditional heteroskedasticity (1986)A Comparison of ARIMA and LSTM in Forecasting Time Series (2018)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)The Performance of LSTM and BiLSTM in Forecasting Time Series (2019)
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References

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  • 2003Forecasting the US unemployment rate

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Cited by

  • 2023Unemployment rate forecasting: LSTM-GRU hybrid approach33 cited
  • 2023Comparison of ARIMA, SutteARIMA, and Holt-Winters, and NNAR Models to Predict Food Grain in India30 cited
  • 2021Unemployment Rates Forecasting with Grey-Based Models in the Post-COVID-19 Period: A Case Study from Vietnam27 cited