IDEAS home Printed from https://ideas.repec.org/f/plu271.html
   My authors  Follow this author

Jani Luoto

Personal Details

First Name:Jani
Middle Name:
Last Name:Luoto
Suffix:
RePEc Short-ID:plu271
[This author has chosen not to make the email address public]
http://blogs.helsinki.fi/jpluoto/home-page/
Terminal Degree:2009 Kauppakorkeakoulu; Jyväskylän yliopisto (from RePEc Genealogy)

Affiliation

(99%) Politiikan ja Talouden Tutkimuksen Laitos
Valtiotieteellinen tiedekunta
Helsingin Yliopisto

Helsinki, Finland
http://www.helsinki.fi/politiikkajatalous/
RePEc:edi:valhefi (more details at EDIRC)

(1%) Helsinki Center for Economic Research (HECER)

Helsinki, Finland
http://www.hecer.fi/
RePEc:edi:hecerfi (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Markku Lanne & Jani Luoto, 2015. "Estimation of DSGE Models under Diffuse Priors and Data-Driven Identification Constraints," CREATES Research Papers 2015-37, Department of Economics and Business Economics, Aarhus University.
  2. Markku Lanne & Jani Luoto, 2014. "Noncausal Bayesian Vector Autoregression," CREATES Research Papers 2014-07, Department of Economics and Business Economics, Aarhus University.
  3. Markku Lanne & Jani Luoto & Henri Nyberg, 2014. "Is the Quantity Theory of Money Useful in Forecasting U.S. Inflation?," CREATES Research Papers 2014-26, Department of Economics and Business Economics, Aarhus University.
  4. Markku Lanne & Jani Luoto, 2013. "A Noncausal Autoregressive Model with Time-Varying Parameters: An Application to U.S. Inflation," Discussion Papers of DIW Berlin 1285, DIW Berlin, German Institute for Economic Research.
  5. Lanne, Markku & Luoto, Jani, 2012. "Does Output Gap, Labor's Share or Unemployment Rate Drive Inflation?," MPRA Paper 41820, University Library of Munich, Germany.
  6. Lanne, Markku & Luoto, Jani, 2011. "Autoregression-Based Estimation of the New Keynesian Phillips Curve," MPRA Paper 29801, University Library of Munich, Germany.
  7. Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2010. "Optimal Forecasting of Noncausal Autoregressive Time Series," MPRA Paper 23648, University Library of Munich, Germany.
  8. Lanne, Markku & Luoto, Jani, 2010. "Has U.S. Inflation Really Become Harder to Forecast?," MPRA Paper 29992, University Library of Munich, Germany.
  9. Lanne, Markku & Luoma, Arto & Luoto, Jani, 2009. "Bayesian Model Selection and Forecasting in Noncausal Autoregressive Models," MPRA Paper 23646, University Library of Munich, Germany.
  10. Lanne, Markku & Luoma, Arto & Luoto, Jani, 2008. "A Naïve Sticky Information Model of Households’ Inflation Expectations," MPRA Paper 8663, University Library of Munich, Germany.
  11. Lanne, Markku & Luoto, Jani, 2007. "Robustness of the Risk-Return Relationship in the U.S. Stock Market," MPRA Paper 3879, University Library of Munich, Germany.
  12. Luoma, Arto & Luoto, Jani & Siivonen, Erkki, 2003. "Growth, Institutions and Productivity: An empirical analysis using the Bayesian approach," Research Reports 104, VATT Institute for Economic Research.

Articles

  1. Markku Lanne & Jani Luoto, 2014. "Does Output Gap, Labour's Share or Unemployment Rate Drive Inflation?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(5), pages 715-726, October.
  2. Lanne, Markku & Luoto, Jani, 2013. "Autoregression-based estimation of the new Keynesian Phillips curve," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 561-570.
  3. Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2012. "Optimal forecasting of noncausal autoregressive time series," International Journal of Forecasting, Elsevier, vol. 28(3), pages 623-631.
  4. Lanne, Markku & Luoto, Jani, 2012. "Has US inflation really become harder to forecast?," Economics Letters, Elsevier, vol. 115(3), pages 383-386.
  5. Markku Lanne & Arto Luoma & Jani Luoto, 2012. "Bayesian Model Selection And Forecasting In Noncausal Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 812-830, August.
  6. Luoto, Jani, 2011. "Aggregate infrastructure capital stock and long-run growth: Evidence from Finnish data," Journal of Development Economics, Elsevier, vol. 94(2), pages 181-191, March.
  7. Lanne, Markku & Luoma, Arto & Luoto, Jani, 2009. "A naïve sticky information model of households' inflation expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 33(6), pages 1332-1344, June.
  8. Arto Luoma & Jani Luoto, 2009. "Modelling the general public's inflation expectations using the Michigan survey data," Applied Economics, Taylor & Francis Journals, vol. 41(10), pages 1311-1320.
  9. Lanne, Markku & Luoto, Jani, 2008. "Robustness of the risk-return relationship in the U.S. stock market," Finance Research Letters, Elsevier, vol. 5(2), pages 118-127, June.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Markku Lanne & Jani Luoto, 2015. "Estimation of DSGE Models under Diffuse Priors and Data-Driven Identification Constraints," CREATES Research Papers 2015-37, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Nalan Baştürk & Stefano Grassi & Lennart Hoogerheide & Herman K. Van Dijk, 2016. "Parallelization Experience with Four Canonical Econometric Models Using ParMitISEM," Econometrics, MDPI, vol. 4(1), pages 1-20, March.
    2. Morris, Stephen D., 2017. "DSGE pileups," Journal of Economic Dynamics and Control, Elsevier, vol. 74(C), pages 56-86.

  2. Markku Lanne & Jani Luoto, 2014. "Noncausal Bayesian Vector Autoregression," CREATES Research Papers 2014-07, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Numan Ülkü & Kexing Wu, 2023. "Stock Market's Response to Real Output Shocks in China: A VARwAL Estimation," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 31(5), pages 1-25, September.
    2. Christian Gourieroux & Joann Jasiak, 2016. "Filtering, Prediction and Simulation Methods for Noncausal Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 405-430, May.
    3. Nelimarkka, Jaakko, 2017. "Evidence on News Shocks under Information Deficiency," MPRA Paper 80850, University Library of Munich, Germany.
    4. Nalan Baştürk & Stefano Grassi & Lennart Hoogerheide & Herman K. Van Dijk, 2016. "Parallelization Experience with Four Canonical Econometric Models Using ParMitISEM," Econometrics, MDPI, vol. 4(1), pages 1-20, March.
    5. Ülkü, Numan & Kuruppuarachchi, Duminda & Kuzmicheva, Olga, 2017. "Stock market's response to real output shocks in Eastern European frontier markets: A VARwAL model," Emerging Markets Review, Elsevier, vol. 33(C), pages 140-154.
    6. Nelimarkka, Jaakko, 2017. "The effects of government spending under anticipation: the noncausal VAR approach," MPRA Paper 81303, University Library of Munich, Germany.

  3. Lanne, Markku & Luoto, Jani, 2012. "Does Output Gap, Labor's Share or Unemployment Rate Drive Inflation?," MPRA Paper 41820, University Library of Munich, Germany.

    Cited by:

    1. Markku Lanne & Jani Luoto, 2016. "Noncausal Bayesian Vector Autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1392-1406, November.
    2. Narayan, Seema & Cirikisuva, Salote & Naivutu, Revoni, 2023. "A hybrid NKPC inflation model for the small Island state of Fiji," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 873-886.
    3. Dustin Chambers & Courtney A. Collins & Alan Krause, 2019. "How do federal regulations affect consumer prices? An analysis of the regressive effects of regulation," Public Choice, Springer, vol. 180(1), pages 57-90, July.
    4. Narayan, Paresh Kumar & Narayan, Seema & Eki Rahman, R. & Setiawan, Iwan, 2019. "Bitcoin price growth and Indonesia's monetary system," Emerging Markets Review, Elsevier, vol. 38(C), pages 364-376.

  4. Lanne, Markku & Luoto, Jani, 2011. "Autoregression-Based Estimation of the New Keynesian Phillips Curve," MPRA Paper 29801, University Library of Munich, Germany.

    Cited by:

    1. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    2. Philip Hans Franses, 2019. "On inflation expectations in the NKPC model," Empirical Economics, Springer, vol. 57(6), pages 1853-1864, December.
    3. Ooft, Gavin & Bhaghoe, Sailesh & Hans Franses, Philip, 2021. "Forecasting annual inflation in Suriname," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    4. Carlos Medel, 2015. "Inflation Dynamics and the Hybrid Neo Keynesian Phillips Curve: The Case of Chile," Working Papers Central Bank of Chile 769, Central Bank of Chile.
    5. Nyberg, Henri & Saikkonen, Pentti, 2012. "Forecasting with a noncausal VAR model," Bank of Finland Research Discussion Papers 33/2012, Bank of Finland.
    6. Weifeng Jin, 2023. "Quantile Autoregression-based Non-causality Testing," Papers 2301.02937, arXiv.org.
    7. Markku Lanne & Jani Luoto, 2019. "A comment on ‘on inflation expectations in the NKPC model’," Empirical Economics, Springer, vol. 57(6), pages 1865-1867, December.
    8. Phiri, Andrew, 2015. "Examining asymmetric effects in the South African Philips curve: Evidence from logistic smooth transition regression (LSTR) models," MPRA Paper 64487, University Library of Munich, Germany.
    9. Alain Hecq & Joao Issler & Elisa Voisin, 2022. "A short term credibility index for central banks under inflation targeting: an application to Brazil," Papers 2205.00924, arXiv.org, revised Jul 2022.
    10. Hecq Alain & Sun Li, 2021. "Selecting between causal and noncausal models with quantile autoregressions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(5), pages 393-416, December.
    11. Zhang, Chengsi & Murasawa, Yasutomo, 2011. "Output gap measurement and the New Keynesian Phillips curve for China," Economic Modelling, Elsevier, vol. 28(6), pages 2462-2468.
    12. Hecq, Alain & Issler, João Victor & Telg, Sean, 2017. "Mixed Causal-Noncausal Autoregressions with Strictly Exogenous Regressors," MPRA Paper 80767, University Library of Munich, Germany.
    13. Alain Hecq & Li Sun, 2019. "Identification of Noncausal Models by Quantile Autoregressions," Papers 1904.05952, arXiv.org.
    14. Alain Hecq & Sean Telg & Lenard Lieb, 2017. "Do Seasonal Adjustments Induce Noncausal Dynamics in Inflation Rates?," Econometrics, MDPI, vol. 5(4), pages 1-22, October.
    15. Kramkov, Viacheslav & Maksimov, Andrey, 2020. "Loan market markups and noncausal autoregressions," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 60, pages 48-69.

  5. Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2010. "Optimal Forecasting of Noncausal Autoregressive Time Series," MPRA Paper 23648, University Library of Munich, Germany.

    Cited by:

    1. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    2. Francisco Blasques & Siem Jan Koopman & Gabriele Mingoli, 2023. "Observation-Driven filters for Time-Series with Stochastic Trends and Mixed Causal Non-Causal Dynamics," Tinbergen Institute Discussion Papers 23-065/III, Tinbergen Institute.
    3. Hecq, A.W. & Lieb, L.M. & Telg, J.M.A., 2015. "Identification of Mixed Causal-Noncausal Models : How Fat Should We Go?," Research Memorandum 035, Maastricht University, Graduate School of Business and Economics (GSBE).
    4. Gianluca Cubadda & Alain Hecq & Sean Telg, 2018. "Detecting Co-Movements in Noncausal Time Series," CEIS Research Paper 430, Tor Vergata University, CEIS, revised 23 Apr 2018.
    5. Henri Nyberg & Markku Lanne & Erkka Saarinen, 2012. "Does noncausality help in forecasting economic time series?," Economics Bulletin, AccessEcon, vol. 32(4), pages 2849-2859.
    6. Karapanagiotidis, Paul, 2013. "Empirical evidence for nonlinearity and irreversibility of commodity futures prices," MPRA Paper 56801, University Library of Munich, Germany.
    7. Hecq, Alain & Voisin, Elisa, 2021. "Forecasting bubbles with mixed causal-noncausal autoregressive models," Econometrics and Statistics, Elsevier, vol. 20(C), pages 29-45.
    8. Saikkonen, Pentti & Sandberg, Rickard, 2013. "Testing for a unit root in noncausal autoregressive models," Bank of Finland Research Discussion Papers 26/2013, Bank of Finland.
    9. Meitz, Mika & Saikkonen, Pentti, 2013. "Maximum likelihood estimation of a noninvertible ARMA model with autoregressive conditional heteroskedasticity," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 227-255.
    10. Matthijs Lof, 2014. "GMM Estimation with Non-causal Instruments under Rational Expectations," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 279-286, April.
    11. Markku Lanne & Jani Luoto, 2016. "Noncausal Bayesian Vector Autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1392-1406, November.
    12. Karapanagiotidis, Paul, 2014. "Dynamic modeling of commodity futures prices," MPRA Paper 56805, University Library of Munich, Germany.
    13. Alain Hecq & Elisa Voisin, 2023. "Predicting Crashes in Oil Prices During The Covid-19 Pandemic with Mixed Causal-Noncausal Models," Advances in Econometrics, in: Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, volume 45, pages 209-233, Emerald Group Publishing Limited.
    14. Christian Gourieroux & Joann Jasiak, 2016. "Filtering, Prediction and Simulation Methods for Noncausal Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 405-430, May.
    15. Dimitrakopoulos, Stefanos, 2017. "Semiparametric Bayesian inference for time-varying parameter regression models with stochastic volatility," Economics Letters, Elsevier, vol. 150(C), pages 10-14.
    16. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.
    17. Lof, Matthijs, 2011. "Noncausality and Asset Pricing," MPRA Paper 30519, University Library of Munich, Germany.
    18. Lanne, Markku & Luoto, Jani, 2012. "Has US inflation really become harder to forecast?," Economics Letters, Elsevier, vol. 115(3), pages 383-386.
    19. Nyberg, Henri & Saikkonen, Pentti, 2012. "Forecasting with a noncausal VAR model," Bank of Finland Research Discussion Papers 33/2012, Bank of Finland.
    20. Lanne Markku & Saikkonen Pentti, 2011. "Noncausal Autoregressions for Economic Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 3(3), pages 1-32, October.
    21. Lanne, Markku & Saikkonen, Pentti, 2009. "Noncausal vector autoregression," Bank of Finland Research Discussion Papers 18/2009, Bank of Finland.
    22. Alain Hecq & Daniel Velasquez-Gaviria, 2022. "Spectral estimation for mixed causal-noncausal autoregressive models," Papers 2211.13830, arXiv.org.
    23. Markku Lanne, 2013. "Noncausality and Inflation Persistence," Discussion Papers of DIW Berlin 1286, DIW Berlin, German Institute for Economic Research.
    24. Weifeng Jin, 2023. "Quantile Autoregression-based Non-causality Testing," Papers 2301.02937, arXiv.org.
    25. Demetrescu, Matei & Kruse, Robinson, 2015. "Testing heteroskedastic time series for normality," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113221, Verein für Socialpolitik / German Economic Association.
    26. Christian Gourieroux & Andrew Hencic & Joann Jasiak, 2021. "Forecast performance and bubble analysis in noncausal MAR(1, 1) processes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 301-326, March.
    27. Lanne, Markku & Luoto, Jani, 2011. "Autoregression-Based Estimation of the New Keynesian Phillips Curve," MPRA Paper 29801, University Library of Munich, Germany.
    28. Fries, Sébastien, 2018. "Conditional moments of noncausal alpha-stable processes and the prediction of bubble crash odds," MPRA Paper 97353, University Library of Munich, Germany, revised Nov 2019.
    29. Christian Gourieroux & Joann Jasiak & Michelle Tong, 2021. "Convolution‐based filtering and forecasting: An application to WTI crude oil prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1230-1244, November.
    30. Alain Hecq & Joao Issler & Elisa Voisin, 2022. "A short term credibility index for central banks under inflation targeting: an application to Brazil," Papers 2205.00924, arXiv.org, revised Jul 2022.
    31. Gourieroux, Christian & Jasiak, Joann, 2018. "Misspecification of noncausal order in autoregressive processes," Journal of Econometrics, Elsevier, vol. 205(1), pages 226-248.
    32. Lof, Matthijs, 2013. "Essays on Expectations and the Econometrics of Asset Pricing," MPRA Paper 59064, University Library of Munich, Germany.
    33. Hecq, Alain & Issler, João Victor & Telg, Sean, 2017. "Mixed Causal-Noncausal Autoregressions with Strictly Exogenous Regressors," MPRA Paper 80767, University Library of Munich, Germany.
    34. Akhter Mohiuddin Rather & V. N. Sastry & Arun Agarwal, 2017. "Stock market prediction and Portfolio selection models: a survey," OPSEARCH, Springer;Operational Research Society of India, vol. 54(3), pages 558-579, September.
    35. Alain Hecq & Li Sun, 2019. "Identification of Noncausal Models by Quantile Autoregressions," Papers 1904.05952, arXiv.org.
    36. Lof, Matthijs & Nyberg, Henri, 2017. "Noncausality and the commodity currency hypothesis," Energy Economics, Elsevier, vol. 65(C), pages 424-433.
    37. Gonçalves Mazzeu, Joao Henrique & Ruiz Ortega, Esther & Veiga, Helena, 2015. "Model uncertainty and the forecast accuracy of ARMA models: A survey," DES - Working Papers. Statistics and Econometrics. WS ws1508, Universidad Carlos III de Madrid. Departamento de Estadística.
    38. Alain Hecq & Sean Telg & Lenard Lieb, 2017. "Do Seasonal Adjustments Induce Noncausal Dynamics in Inflation Rates?," Econometrics, MDPI, vol. 5(4), pages 1-22, October.
    39. Lanne, Markku & Nyberg, Henri & Saarinen, Erkka, 2011. "Forecasting U.S. Macroeconomic and Financial Time Series with Noncausal and Causal AR Models: A Comparison," MPRA Paper 30254, University Library of Munich, Germany.

  6. Lanne, Markku & Luoto, Jani, 2010. "Has U.S. Inflation Really Become Harder to Forecast?," MPRA Paper 29992, University Library of Munich, Germany.

    Cited by:

    1. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    2. Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2010. "Optimal Forecasting of Noncausal Autoregressive Time Series," MPRA Paper 23648, University Library of Munich, Germany.
    3. Alain Hecq & Daniel Velasquez-Gaviria, 2022. "Spectral estimation for mixed causal-noncausal autoregressive models," Papers 2211.13830, arXiv.org.
    4. Markku Lanne, 2013. "Noncausality and Inflation Persistence," Discussion Papers of DIW Berlin 1286, DIW Berlin, German Institute for Economic Research.
    5. Bao Yong & Zhang Ru, 2013. "Estimation Bias and Feasible Conditional Forecasts from the First-Order Moving Average Model," Journal of Time Series Econometrics, De Gruyter, vol. 6(1), pages 63-80, July.

  7. Lanne, Markku & Luoma, Arto & Luoto, Jani, 2009. "Bayesian Model Selection and Forecasting in Noncausal Autoregressive Models," MPRA Paper 23646, University Library of Munich, Germany.

    Cited by:

    1. Markku Lanne & Jani Luoto, 2017. "A New Time‐Varying Parameter Autoregressive Model for U.S. Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(5), pages 969-995, August.
    2. Henri Nyberg & Markku Lanne & Erkka Saarinen, 2012. "Does noncausality help in forecasting economic time series?," Economics Bulletin, AccessEcon, vol. 32(4), pages 2849-2859.
    3. Saikkonen, Pentti & Sandberg, Rickard, 2013. "Testing for a unit root in noncausal autoregressive models," Bank of Finland Research Discussion Papers 26/2013, Bank of Finland.
    4. Frédérique Bec & Heino Bohn Nielsen & Sarra Saïdi, 2020. "Mixed Causal–Noncausal Autoregressions: Bimodality Issues in Estimation and Unit Root Testing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1413-1428, December.
    5. Joshua C.C. Chan & Angelia L. Grant, 2015. "Pitfalls of Estimating the Marginal Likelihood Using the Modified Harmonic Mean," CAMA Working Papers 2015-08, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    6. Markku Lanne & Jani Luoto, 2016. "Noncausal Bayesian Vector Autoregression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1392-1406, November.
    7. Christian Gourieroux & Joann Jasiak, 2016. "Filtering, Prediction and Simulation Methods for Noncausal Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 405-430, May.
    8. Lof, Matthijs, 2011. "Noncausality and Asset Pricing," MPRA Paper 30519, University Library of Munich, Germany.
    9. Lanne, Markku & Luoto, Jani, 2012. "Has US inflation really become harder to forecast?," Economics Letters, Elsevier, vol. 115(3), pages 383-386.
    10. Nyberg, Henri & Saikkonen, Pentti, 2012. "Forecasting with a noncausal VAR model," Bank of Finland Research Discussion Papers 33/2012, Bank of Finland.
    11. Frédérique Bec & Alain Guay & Heino Bohn Nielsen & Sarra Saïdi, 2022. "Power of unit root tests against nonlinear and noncausal alternatives," THEMA Working Papers 2022-14, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    12. Markku Lanne, 2013. "Noncausality and Inflation Persistence," Discussion Papers of DIW Berlin 1286, DIW Berlin, German Institute for Economic Research.
    13. Christian Gourieroux & Andrew Hencic & Joann Jasiak, 2021. "Forecast performance and bubble analysis in noncausal MAR(1, 1) processes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(2), pages 301-326, March.
    14. Lanne, Markku & Luoto, Jani, 2011. "Autoregression-Based Estimation of the New Keynesian Phillips Curve," MPRA Paper 29801, University Library of Munich, Germany.
    15. Christian Gourieroux & Joann Jasiak & Michelle Tong, 2021. "Convolution‐based filtering and forecasting: An application to WTI crude oil prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1230-1244, November.
    16. Jean-Baptiste MICHAU, 2019. "Helicopter Drops of Money under Secular Stagnation," Working Papers 2019-10, Center for Research in Economics and Statistics.
    17. Lof, Matthijs, 2013. "Essays on Expectations and the Econometrics of Asset Pricing," MPRA Paper 59064, University Library of Munich, Germany.
    18. Lanne, Markku & Nyberg, Henri & Saarinen, Erkka, 2011. "Forecasting U.S. Macroeconomic and Financial Time Series with Noncausal and Causal AR Models: A Comparison," MPRA Paper 30254, University Library of Munich, Germany.

  8. Lanne, Markku & Luoma, Arto & Luoto, Jani, 2008. "A Naïve Sticky Information Model of Households’ Inflation Expectations," MPRA Paper 8663, University Library of Munich, Germany.

    Cited by:

    1. Pfajfar, D. & Santoro, E., 2012. "News on Inflation and the Epidemiology of Inflation Expectations," Other publications TiSEM 515ee09e-b946-439f-afff-d, Tilburg University, School of Economics and Management.
    2. Camille Cornand & Cheick Kader M'Baye, 2016. "Band or Point Inflation Targeting? An Experimental Approach," Working Papers halshs-01313095, HAL.
    3. Carrera, César, 2012. "Estimating Information Rigidity using Firms’ Survey Data," Working Papers 2012-004, Banco Central de Reserva del Perú.
    4. Cornand, Camille & Hubert, Paul, 2020. "On the external validity of experimental inflation forecasts: A comparison with five categories of field expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    5. Olivier Armantier & Scott Nelson & Giorgio Topa & Wilbert van der Klaauw & Basit Zafar, 2016. "The Price Is Right: Updating Inflation Expectations in a Randomized Price Information Experiment," The Review of Economics and Statistics, MIT Press, vol. 98(3), pages 503-523, July.
    6. Paul Hubert, 2014. "FOMC Forecasts as a Focal Point for Private Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(7), pages 1381-1420, October.
    7. OKIMOTO Tatsuyoshi, 2018. "Trend Inflation and Monetary Policy Regimes in Japan," Discussion papers 18024, Research Institute of Economy, Trade and Industry (RIETI).
    8. Yingying XU & Zhixin LIU & Jaime ORTIZ, 2018. "Actual and Expected Inflation in the U.S.: A Time-Frequency View," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 42-62, December.
    9. Camille Cornand & Paul Hubert, 2020. "On the external validity of experimental inflation forecasts," Post-Print hal-02894262, HAL.
    10. Easaw Joshy & Golinelli Roberto, 2010. "Households Forming Inflation Expectations: Active and Passive Absorption Rates," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-32, November.
    11. J. Easaw & R. Golinelli & M. Malgarini, 2012. "Do Households Anchor their Inflation Expectations? Theory and Evidence from a Household Survey," Working Papers wp842, Dipartimento Scienze Economiche, Universita' di Bologna.
    12. Beqiraj, Elton & Di Bartolomeo, Giovanni & Di Pietro, Marco, 2019. "Beliefs formation and the puzzle of forward guidance power," Journal of Macroeconomics, Elsevier, vol. 60(C), pages 20-32.
    13. Charles Bellemare & Rolande Kpekou Tossou & Kevin Moran, 2020. "The Determinants of Consumers' Inflation Expectations: Evidence from the US and Canada," Staff Working Papers 20-52, Bank of Canada.
    14. Paul Hubert & Harun Mirza, 2019. "The role of forward- and backward-looking information for inflation expectations formation," Post-Print hal-03403616, HAL.
    15. Easaw, Joshy & Golinelli, Roberto & Malgarini, Marco, 2013. "What determines households inflation expectations? Theory and evidence from a household survey," European Economic Review, Elsevier, vol. 61(C), pages 1-13.
    16. Yingying Xu & Zhixin Liu & Xing Zhang, 2017. "Heterogeneous Or Homogeneous Inflation Expectation Formation Models: A Case Study Of Chinese Households And Financial Participants," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 62(04), pages 859-874, September.
    17. Steinbacher, Mitja & Raddant, Matthias & Karimi, Fariba & Camacho-Cuena, Eva & Alfarano, Simone & Iori, Giulia & Lux, Thomas, 2021. "Advances in the Agent-Based Modeling of Economic and Social Behavior," MPRA Paper 107317, University Library of Munich, Germany.
    18. Guzman, Giselle C., 2010. "An inflation expectations horserace," MPRA Paper 36511, University Library of Munich, Germany.
    19. Easaw, Joshy, 2015. "Household Forming Inflation Expectations: Why Do They Overreact ?," Cardiff Economics Working Papers E2015/14, Cardiff University, Cardiff Business School, Economics Section.
    20. Li, You & Tay, Anthony, 2021. "The role of macroeconomic and policy uncertainty in density forecast dispersion," Journal of Macroeconomics, Elsevier, vol. 67(C).
    21. Marine Charlotte André & Meixing Dai, 2017. "Learning, optimal monetary delegation and stock prices dynamics," Working Papers of BETA 2017-37, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    22. Camille Cornand & Paul Hubert, 2019. "On the external validity of experimental inflation forecasts: A comparison with five categories of field expectations: A comparison with five categories of field expectations," Sciences Po publications 03, Sciences Po.
    23. Xu, Yingying & Chang, Hsu-Ling & Lobonţ, Oana-Ramona & Su, Chi-Wei, 2016. "Modeling heterogeneous inflation expectations: empirical evidence from demographic data?," Economic Modelling, Elsevier, vol. 57(C), pages 153-163.
    24. Yingying Xu & Zhi-Xin Liu & Hsu-Ling Chang & Adelina Dumitrescu Peculea & Chi-Wei Su, 2017. "Does self-fulfilment of the inflation expectation exist?," Applied Economics, Taylor & Francis Journals, vol. 49(11), pages 1098-1113, March.
    25. Guzman, Giselle C., 2011. "The case for higher frequency inflation expectations," MPRA Paper 36656, University Library of Munich, Germany.

  9. Lanne, Markku & Luoto, Jani, 2007. "Robustness of the Risk-Return Relationship in the U.S. Stock Market," MPRA Paper 3879, University Library of Munich, Germany.

    Cited by:

    1. David Ardia & Lennart F. Hoogerheide, 2010. "Efficient Bayesian Estimation and Combination of GARCH-Type Models," Tinbergen Institute Discussion Papers 10-046/4, Tinbergen Institute.
    2. Lanne, Markku & Luoto, Jani, 2007. "Robustness of the Risk-Return Relationship in the U.S. Stock Market," MPRA Paper 3879, University Library of Munich, Germany.
    3. Richard A. Michelfelder, 2014. "Asset characteristics of solar renewable energy certificates: market solution to encourage environmental sustainability," Journal of Sustainable Finance & Investment, Taylor & Francis Journals, vol. 4(3), pages 280-296, July.
    4. Jiranyakul, Komain, 2011. "On the Risk-Return Tradeoff in the Stock Exchange of Thailand: New Evidence," MPRA Paper 45583, University Library of Munich, Germany.
    5. Mohanty, Roshni & P, Srinivasan, 2014. "The Time-Varying Risk and Return Trade Off in Indian Stock Markets," MPRA Paper 55660, University Library of Munich, Germany.
    6. Michelfelder, Richard A., 2015. "Empirical analysis of the generalized consumption asset pricing model: Estimating the cost of capital," Journal of Economics and Business, Elsevier, vol. 80(C), pages 37-50.
    7. Pauline Ahern & Frank Hanley & Richard Michelfelder, 2011. "New approach to estimating the cost of common equity capital for public utilities," Journal of Regulatory Economics, Springer, vol. 40(3), pages 261-278, December.
    8. Arshanapalli, Bala & Fabozzi, Frank J. & Nelson, William, 2013. "The role of jump dynamics in the risk–return relationship," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 212-218.

  10. Luoma, Arto & Luoto, Jani & Siivonen, Erkki, 2003. "Growth, Institutions and Productivity: An empirical analysis using the Bayesian approach," Research Reports 104, VATT Institute for Economic Research.

    Cited by:

    1. Järviö, Maija-Liisa & Luoma, Kalevi & Räty, Tarmo & Aaltonen, Juho, 2005. "Productivity and its Drivers in Finnish Primary Care 1988-2003," Research Reports 118, VATT Institute for Economic Research.
    2. Jan-Erik Antipin & George Mavrotas, 2006. "On the Empirics of Aid and Growth: A Fresh Look," WIDER Working Paper Series RP2006-05, World Institute for Development Economic Research (UNU-WIDER).

Articles

  1. Markku Lanne & Jani Luoto, 2014. "Does Output Gap, Labour's Share or Unemployment Rate Drive Inflation?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(5), pages 715-726, October.
    See citations under working paper version above.
  2. Lanne, Markku & Luoto, Jani, 2013. "Autoregression-based estimation of the new Keynesian Phillips curve," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 561-570.
    See citations under working paper version above.
  3. Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2012. "Optimal forecasting of noncausal autoregressive time series," International Journal of Forecasting, Elsevier, vol. 28(3), pages 623-631.
    See citations under working paper version above.
  4. Lanne, Markku & Luoto, Jani, 2012. "Has US inflation really become harder to forecast?," Economics Letters, Elsevier, vol. 115(3), pages 383-386.
    See citations under working paper version above.
  5. Markku Lanne & Arto Luoma & Jani Luoto, 2012. "Bayesian Model Selection And Forecasting In Noncausal Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 812-830, August.
    See citations under working paper version above.
  6. Luoto, Jani, 2011. "Aggregate infrastructure capital stock and long-run growth: Evidence from Finnish data," Journal of Development Economics, Elsevier, vol. 94(2), pages 181-191, March.

    Cited by:

    1. Augustin Kwasi Fosu & Yoseph Yilma Getachew & Thomas Ziesemer, 2012. "Optimal public investment, growth and consumption: evidence from African countries," Global Development Institute Working Paper Series 16412, GDI, The University of Manchester.
    2. Xavier Tafunell & Cristián Ducoing, 2015. "Non-residential capital stock in Latin America. 1875-2008," Economics Working Papers 1472, Department of Economics and Business, Universitat Pompeu Fabra.
    3. Krüger, Niclas, 2012. "Does infrastructure really cause growth?: the time scale dependent causality nexus between infrastructure investments and GDP," Working papers in Transport Economics 2012:15, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    4. Augustin K. Fosu & Thomas H. W. Ziesemer & Yoseph Y. Getachew, 2014. "Optimal Public Investment, Growth, and Consumption: Fresh Evidence from African Countries," Working Papers 471, Economic Research Southern Africa.
    5. Emmanuel Apergis & Nicholas Apergis, 2019. "“Sakura” has not grown in a day: infrastructure investment and economic growth in Japan under different tax regimes," Empirical Economics, Springer, vol. 57(2), pages 541-567, August.
    6. Hallonsten, Jan Simon & Ziesemer, Thomas, 2016. "A semi-endogenous growth model for developing countries with public factors, imported capital goods, and limited export demand," MERIT Working Papers 2016-004, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).

  7. Lanne, Markku & Luoma, Arto & Luoto, Jani, 2009. "A naïve sticky information model of households' inflation expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 33(6), pages 1332-1344, June.
    See citations under working paper version above.
  8. Arto Luoma & Jani Luoto, 2009. "Modelling the general public's inflation expectations using the Michigan survey data," Applied Economics, Taylor & Francis Journals, vol. 41(10), pages 1311-1320.

    Cited by:

    1. Menz, Jan-Oliver & Poppitz, Philipp, 2013. "Household`s Disagreement on Inflation Expectations and Socioeconomic Media Exposure in Germany," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 80006, Verein für Socialpolitik / German Economic Association.

  9. Lanne, Markku & Luoto, Jani, 2008. "Robustness of the risk-return relationship in the U.S. stock market," Finance Research Letters, Elsevier, vol. 5(2), pages 118-127, June.
    See citations under working paper version above.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 10 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (7) 2010-07-17 2010-07-17 2011-04-09 2012-10-20 2013-03-30 2014-04-05 2016-03-06. Author is listed
  2. NEP-CBA: Central Banking (5) 2008-05-10 2010-07-17 2010-07-17 2011-04-09 2014-09-05. Author is listed
  3. NEP-MAC: Macroeconomics (5) 2008-05-10 2011-04-09 2012-10-20 2014-04-05 2014-09-05. Author is listed
  4. NEP-ETS: Econometric Time Series (4) 2010-07-17 2010-07-17 2013-03-30 2014-04-05
  5. NEP-FOR: Forecasting (4) 2010-07-17 2010-07-17 2014-04-05 2016-03-06
  6. NEP-MON: Monetary Economics (2) 2013-03-30 2014-09-05
  7. NEP-ORE: Operations Research (2) 2010-07-17 2010-07-17
  8. NEP-DGE: Dynamic General Equilibrium (1) 2016-03-06
  9. NEP-FMK: Financial Markets (1) 2007-07-13
  10. NEP-RMG: Risk Management (1) 2007-07-13

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Jani Luoto should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.