SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Inflation forecasting in an emerging economy: selecting variables with machine learning algorithms
16 references·1 citing·57 second hop
Inflation forecasting in an emerging economy: selecting variables with machine learning algorithms (2021)Inflation forecasting in an emerging econ…Macroeconomic forecast accuracy in a data‐rich environment (2019)Macroeconomic forecast accura…Forecasting Inflation in a Data-Rich Environment: The Benefits of Machine Learning Methods (2019)Forecasting Inflation in a Da…Inflation Forecasting Using Machine Learning Methods (2018)Inflation Forecasting Using M…A Phillips Curve with Anchored Expectations and Short‐Term Unemployment (2018)A Phillips Curve with Anchore…Real-time inflation forecasting with high-dimensional models: The case of Brazil (2017)Real-time inflation forecasti…Machine Learning at Central Banks (2017)Machine Learning at Central B…Forecasting inflation using survey expectations and target inflation: Evidence for Brazil and Turkey (2015)Forecasting inflation using s…A Comparative Study on the Effects of Oil Price Changes on Inflation (2015)A Comparative Study on the Ef…Short-term inflation forecasting models for Turkey and a forecast combination analysis (2013)Short-term inflation forecast…Real‐Time Forecasts of Inflation: The Role of Financial Variables (2012)Real‐Time Forecasts of Inflat…Real-Time Inflation Forecasting in a Changing World (2012)Real-Time Inflation Forecasti…Do financial variables help forecasting inflation and real activity in the euro area? (2003)Do financial variables help f…Exchange Rate Pass-Through in Turkey (2002)Exchange Rate Pass-Through in…An introduction to statistical finance (2002)An introduction to statistica…Are Phillips Curves Useful for Forecasting Inflation? (2001)Are Phillips Curves Useful fo…Forecasting inflation (1999)Forecasting inflationInflation and stock market growth: the case of IPO withdrawal (2023)Inflation and stock market gr…Pooled Mean Group Estimation of Dynamic Heterogeneous Panels (1999)What is an Oil Shock? (2000)Are Oil Shocks Inflationary?: Asymmetric and Nonlinear Specifications versus Changes in Regime (2002)Influence of oil prices on inflation in South Asia: Some new evidence (2021)The asymmetric impacts of oil price and shocks on inflation in BRICS: a multiple threshold nonlinear ARDL model (2021)Geopolitical risks, oil price shocks and inflation: Evidence from a TVP–SV–VAR approach (2023)A long memory property of stock market returns and a new model (1993)Introduction to Econophysics (1999)Empirical properties of asset returns: stylized facts and statistical issues (2001)Causes of Variation in Construction Project Task Starting Times and Duration (2011)Quantifying China’s regional economic complexity (2017)Machine learning for environmental monitoring (2018)The Generalized Dynamic-Factor Model: Identification and Estimation (2000)Forecasting Output and Inflation: The Role of Asset Prices (2001)Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions (2006)Determining the Number of Factors in the General Dynamic Factor Model (2007)Now-Casting and the Real-Time Data Flow (2013)Comparing Predictive Accuracy (1994)Macroeconomic Forecasting Using Diffusion Indexes (2002)INTEREST AND PRICES: FOUNDATIONS OF A THEORY OF MONETARY POLICY (2005)Family Background, Self-Confidence and Economic Outcomes (2012)Public Expenditure Distribution, Voting, and Growth (2014)INEQUALITY AND TRUST: NEW EVIDENCE FROM PANEL DATA (2015)Chapter 4 Forecast Combinations (2006)Big data: a revolution that will transform how we live, work, and think (2013)Big Data: New Tricks for Econometrics (2014)An interdisciplinary model for macroeconomics (2017)Drawing on different disciplines: macroeconomic agent-based models (2018)Nowcasting GDP using machine-learning algorithms: A real-time assessment (2020)The Impact of Uncertainty Shocks (2009)Measuring Uncertainty (2015)Forecasting of Real GDP Growth Using Machine Learning Models: Gradient Boosting and Random Forest Approach (2020)How is machine learning useful for macroeconomic forecasting? (2022)Targeting predictors in random forest regression (2022)Aggregate Dynamics and Staggered Contracts (1980)The Role of Monetary Policy (1995)Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory* (2000)Disagreement about Inflation Expectations (2003)Globalisation and Inflation: New Cross-Country Evidence on the Global Determinants of Domestic Inflation (2007)Inflation-Gap Persistence in the US (2009)Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy (2005)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)Complete subset regressions (2013)Macroeconomic Forecasting Performance under Alternative Specifications of Time-Varying Volatility (2014)Forecasting realized volatility in a changing world: A dynamic model averaging approach (2015)The Relation Between Unemployment and the Rate of Change of Money Wage Rates in the United Kingdom, 1861–1957 1 (1958)Discretion versus policy rules in practice (1993)Tests for Parameter Instability and Structural Change With Unknown Change Point (1993)Strategic Mapping of Youth Unemployment With Interval-Valued Intuitionistic Hesitant Fuzzy DEMATEL Based on 2-Tuple Linguistic Values (2020)Taking the Fed at its Word: A New Approach to Estimating Central Bank Objectives using Text Analysis (2021)Understanding U.S. Inflation During the COVID Era (2022)Interpreting the macroeconomic time series facts (1992)Efficient Tests for an Autoregressive Unit Root (1996)Postwar U.S. Business Cycles: An Empirical Investigation (1997)Determining the Number of Factors in Approximate Factor Models (2002)Inferential Theory for Factor Models of Large Dimensions (2003)Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy (2009)
this work references cited by second hop

References

  • 1999Forecasting inflation1,273 cited
  • 2001Are Phillips Curves Useful for Forecasting Inflation?731 cited
  • 2019Forecasting Inflation in a Data-Rich Environment: The Benefits of Machine Learning Methods385 cited
  • 2002An introduction to statistical finance348 cited
  • 2003Do financial variables help forecasting inflation and real activity in the euro area?336 cited
  • 2012Real‐Time Forecasts of Inflation: The Role of Financial Variables222 cited
  • 2012Real-Time Inflation Forecasting in a Changing World195 cited
  • 2017Machine Learning at Central Banks138 cited
  • 2018A Phillips Curve with Anchored Expectations and Short‐Term Unemployment126 cited
  • 2015A Comparative Study on the Effects of Oil Price Changes on Inflation126 cited
  • 2002Exchange Rate Pass-Through in Turkey113 cited
  • 2017Real-time inflation forecasting with high-dimensional models: The case of Brazil94 cited
  • 2019Macroeconomic forecast accuracy in a data‐rich environment61 cited
  • 2018Inflation Forecasting Using Machine Learning Methods48 cited
  • 2013Short-term inflation forecasting models for Turkey and a forecast combination analysis45 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

  • 2015Forecasting inflation using survey expectations and target inflation: Evidence for Brazil and Turkey40 cited
  • Cited by

    • 2023Inflation and stock market growth: the case of IPO withdrawal14 cited