FOCUS ON EUROPEAN ECONOMIC INTEGRATION Q1/19

[1]  Karl Pearson F.R.S..  LIII. On lines and planes of closest fit to systems of points in space , 1901 .

[2]  H. Hotelling.  Analysis of a complex of statistical variables into principal components. , 1933 .

[3]  A. Roy.  Some thoughts on the distribution of earnings , 1951 .

[4]  L. Sjaastad.  The Costs and Returns of Human Migration , 1962 .

[5]  G. Becker,et al.  Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education, Third Edition , 1993 .

[6]  Robert B. Litterman,et al.  Forecasting and Conditional Projection Using Realistic Prior Distributions , 1983 .

[7]  Robert B. Litterman.  Forecasting with Bayesian Vector Autoregressions-Five Years of Experience , 1984 .

[8]  G. Borjas.  Self-Selection and the Earnings of Immigrants , 1987, Foundations of Migration Economics.

[9]  C. Manski.  The Use of Intentions Data to Predict Behavior: A Best-Case Analysis , 1990 .

[10]  Peter E. Rossi,et al.  Bayesian Analysis of Stochastic Volatility Models , 1994 .

[11]  N. Shephard,et al.  Stochastic Volatility: Likelihood Inference And Comparison With Arch Models , 1996 .

[12]  Ian Richard Gordon,et al.  Duration Dependence in Migration Behaviour: Cumulative Inertia versus Stochastic Change , 1995, Environment & planning A.

[13]  D. Sandu,et al.  Migration in market and democracy transition: Migration intentions and behavior in Romania , 1996 .

[14]  C. Sims,et al.  Bayesian methods for dynamic multivariate models , 1998 .

[15]  B. Chiswick.  Are Immigrants Favorably Self-Selected? , 1999 .

[16]  F. Docquier,et al.  Brain drain and economic growth: theory and evidence , 2001 .

[17]  Mark P. Taylor,et al.  Tied Down or Room to Move? Investigating the Relationships between Housing Tenure, Employment Status and Residential Mobility in Britain , 2002 .

[18]  C. Dustmann.  Children and return migration , 2003 .

[19]  T. Sargent,et al.  Drifts and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S. , 2003 .

[20]  K. Hubrich.  Forecasting Euro Area Inflation: Does Aggregating Forecasts by Hicp Component Improve Forecast Accuracy? , 2003 .

[21]  J. Stock,et al.  Macroeconomic forecasting in the Euro area: Country specific versus area-wide information , 2003 .

[22]  Giorgio E. Primiceri.  Time Varying Structural Vector Autoregressions and Monetary Policy , 2002 .

[23]  Stanislav KolenikovGustavo Angeles.  The Use of Discrete Data in PCA: Theory, Simulations, and Applications to Socioeconomic Indices , 2004 .

[24]  T. Liebig,et al.  Migration, Self-Selection and Income Inequality: An International Analysis , 2004 .

[25]  A. Timmermann.  Forecast Combinations , 2005 .

[26]  D. Hendry,et al.  Forecasting Economic Aggregates by Disaggregates , 2006, SSRN Electronic Journal.

[27]  P. Ester,et al.  Factors determining international and regional Migration in Europe. , 2007 .

[28]  M. Todaro,et al.  Migration, Unemployment and Developmnent: A Two-Sector Analysis , 2007 .

[29]  J. Geweke,et al.  Comparing and Evaluating Bayesian Predictive Distributions of Asset Returns , 2008 .

[30]  P. Ester,et al.  How willing are Europeans to migrate? a comparison of migration intentions in Western and Eastern Europe , 2008 .

[31]  J. Geweke,et al.  Optimal Prediction Pools , 2008 .

[32]  D. Hendry,et al.  Combining Disaggregate Forecasts or Combining Disaggregate Information to Forecast an Aggregate , 2009, SSRN Electronic Journal.

[33]  G. Kapetanios,et al.  Forecasting Large Datasets with Bayesian Reduced Rank Multivariate Models , 2009 .

[34]  Antonello D’Agostino,et al.  Macroeconomic Forecasting and Structural Change , 2009, SSRN Electronic Journal.

[35]  Simple but Effective: The OeNB’s Forecasting Model for Selected CESEE Countries , 2009 .

[36]  H. Lütkepohl.  Forecasting Nonlinear Aggregates and Aggregates with Time-varying Weights , 2010, SSRN Electronic Journal.

[37]  Antonello D’Agostino,et al.  Understanding and forecasting aggregate and disaggregate price dynamics , 2011, SSRN Electronic Journal.

[38]  D. Giannone,et al.  Large Bayesian vector auto regressions , 2010 .

[39]  J. Griffin,et al.  Inference with normal-gamma prior distributions in regression problems , 2010 .

[40]  F. Docquier,et al.  A Panel Data Analysis of the Brain Gain , 2011 .

[41]  Todd E. Clark,et al.  Bayesian VARs: Specification Choices and Forecast Accuracy , 2011 .

[42]  Andrzej Kocięcki,et al.  Predictivistic Bayesian Forecasting System , 2011 .

[43]  B. Miguel,et al.  Hierarchical shrinkage in time-varying parameter models , 2011 .

[44]  Paulo Júlio,et al.  Evaluating the forecast quality of GDP components: An application to G7 , 2012 .

[45]  G. Koop.  Forecasting with Medium and Large Bayesian VARs , 2013 .

[46]  Mathew J. Creighton.  The role of aspirations in domestic and international migration , 2013 .

[47]  Shaun P. Vahey,et al.  Forecast densities for economic aggregates from disaggregate ensembles , 2010 .

[48]  H. Lütkepohl,et al.  Forecasting Contemporaneous Aggregates with Stochastic Aggregation Weights , 2013 .

[49]  G. Peri,et al.  The Cross-country Determinants of Potential and Actual Migration 1 , 2014 .

[50]  Davor Kunovac,et al.  Nowcasting GDP Using Available Monthly Indicators , 2014 .

[51]  T. Berg,et al.  Point and Density Forecasts for the Euro Area Using Bayesian VARs , 2014, SSRN Electronic Journal.

[52]  Vladimir Otrachshenko,et al.  Life (Dis)Satisfaction and the Intention to Migrate: Evidence from Central and Eastern Europe , 2014 .

[53]  Todd E. Clark,et al.  Have Standard VARs Remained Stable Since the Crisis? , 2014 .

[54]  Gregor Kastner,et al.  Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models , 2014, Comput. Stat. Data Anal..

[55]  Can Trade Partners Help Better Forcee the Future? Impact of Trade Linkages on Economic Growth Forecasts in Selected Cesee Countries , 2014 .

[56]  Short-Term Forecasting of GDP under Structural Changes , 2014 .

[57]  Marco Del Negro,et al.  Common Drifting Volatility in Large Bayesian VARs ∗ , 2015 .

[58]  Todd E. Clark,et al.  Macroeconomic Forecasting Performance under Alternative Specifications of Time-Varying Volatility , 2015 .

[59]  Felix I. Lessambo,et al.  The European Bank for Reconstruction and Development , 1990 .

[60]  Florian Huber,et al.  Forecasting with Global Vector Autoregressive Models: a Bayesian Approach , 2016 .

[61]  Michal Franta,et al.  Forecasting Czech GDP Using Mixed-Frequency Data Models , 2016 .

[62]  R. Atoyan,et al.  Emigration and Its Economic Impact on Eastern Europe , 2016 .

[63]  Joshua C. C. Chan,et al.  Stochastic Model Specification Search for Time-Varying Parameter VARs , 2014 .

[64]  Gregor Kastner,et al.  Dealing with Stochastic Volatility in Time Series Using the R Package stochvol , 2016, 1906.12134.

[65]  A. Raggl.  Migration intentions in CESEE – a descriptive analysis , 2017 .

[66]  Michal Franta,et al.  A BVAR Model for Forecasting of Czech Inflation , 2017 .

[67]  Xin Meng,et al.  Risk Attitudes and Household Migration Decisions , 2017, The Journal of Human Resources.

[68]  J. Andrei,et al.  A multifactor approach to forecasting Romanian gross domestic product (GDP) in the short run , 2017, PloS one.

[69]  M. Piracha,et al.  Remittances and migration intentions of the left-behind , 2017, SSRN Electronic Journal.

[70]  D. Hendry,et al.  The future of macroeconomics: Macro theory and models at the Bank of England , 2018 .

[71]  Joshua C. C. Chan,et al.  Bayesian Model Comparison for Time-Varying Parameter VARs with Stochastic Volatility , 2015 .

[72]  A simple approach to nowcasting GDP growth in CESEE economies , 2018 .

[73]  Marcin Kolasa,et al.  Does the foreign sector help forecast domestic variables in DSGE models? , 2016, International Journal of Forecasting.

[74]  Richard Grieveson.  Demographic decline does not necessarily condemn CESEE EU countries to a low growth future , 2018 .

[75]  Florian Huber,et al.  Adaptive Shrinkage in Bayesian Vector Autoregressive Models , 2019 .

[76]  Florian Huber,et al.  Should I stay or should I go? A latent threshold approach to large‐scale mixture innovation models , 2016, Journal of Applied Econometrics.

[77]  Sylvia Fruhwirth-Schnatter,et al.  Achieving shrinkage in a time-varying parameter model framework , 2016, Journal of Econometrics.

[78]  G. Kastner.  Sparse Bayesian time-varying covariance estimation in many dimensions , 2016, Journal of Econometrics.