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  1. Sieve bootstrap inference for time-varying coefficient models
    Autor*in: Friedrich, Marina; Lin, Yicong
    Erschienen: [2021]
    Verlag:  Tinbergen Institute, Amsterdam, The Netherlands

    We propose a sieve bootstrap framework to conduct pointwise and simultaneous inference for time-varying coefficient regression models based on a nonparametric local linear estimator. The asymptotic validity of the sieve bootstrap in the presence of... mehr

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    We propose a sieve bootstrap framework to conduct pointwise and simultaneous inference for time-varying coefficient regression models based on a nonparametric local linear estimator. The asymptotic validity of the sieve bootstrap in the presence of autocorrelation is established. We find that it automatically produces a consistent estimation of nuisance parameters, both at the interior and boundary points. In addition, we develop a bootstrap test for parameter constancy and show that it is asymptotically correctly sized. An extensive simulation study supports our findings. The proposed methods are applied to assess the price development of CO2 certificates in the European Emissions Trading System (EU ETS). We find evidence of time variation in the relationship between allowance prices and their fundamental price drivers.

     
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    Sprache: Englisch
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    Weitere Identifier:
    hdl: 10419/248789
    Schriftenreihe: Array ; TI 2021, 107
    Schlagworte: sieve bootstrap; nonparametric estimation; simultaneous confidence bands; energy economics; emission trading
    Umfang: 1 Online-Ressource (circa 55 Seiten), Illustrationen
  2. Estimating density ratio of marginals to joint
    applications to causal inference
    Autor*in: Matsushita, Yukitoshi; Otsu, Taisuke; Takahata, Keisuke
    Erschienen: [2022]
    Verlag:  LSE, STICERD, London

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    Schriftenreihe: Econometrics papers / LSE ; STICERD ; paper number EM619
    Schlagworte: density ratio; causal inference; nonparametric estimation
    Umfang: 1 Online-Ressource (39 Seiten)
  3. Nonlinear budget set regressions for the random utility model
    Autor*in: Blomquist, Nils Sören; Kumar, Anil; Liang, Che-yuan; Newey, Whitney K.
    Erschienen: September 2022
    Verlag:  Federal Reserve Bank of Dallas, Research Department, Dallas

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    Schriftenreihe: Working paper / Federal Reserve Bank of Dallas, Research Department ; 2219
    Schlagworte: Nonlinear budget sets; nonparametric estimation; heterogeneous preferences; taxable income; revealed stochastic preference
    Umfang: 1 Online-Ressource (circa 54 Seiten), Illustrationen
  4. Global Evidence on Profit Shifting Within Firms and Across Time
    Autor*in: Delis, Fotis; Delēs, Manthos D.; Laeven, Luc; Ongena, Steven
    Erschienen: 2022
    Verlag:  SSRN, [S.l.]

    We provide the first global estimates of profit shifting at the subsidiary-year level. Employing nonparametric estimation techniques within a mainstay model of profit shifting, we examine the subsidiary-year responses of earnings to the composite tax... mehr

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    We provide the first global estimates of profit shifting at the subsidiary-year level. Employing nonparametric estimation techniques within a mainstay model of profit shifting, we examine the subsidiary-year responses of earnings to the composite tax indicator faced by all subsidiaries of a multinational firm. Our panel includes 26,593 subsidiaries across 95 countries for the period 2009 2017. We extensively validate our results against aggregate estimates of previous studies and evidence from specific cases. We find that profit shifting decreased over this period in advanced economies but increased in other parts of the world where taxation policies are less stringent on average, consistent with tax arbitrage strategies. We also examine correlates of profit shifting, identifying that a key determinant is the subsidiaries’ ratio of intangible assets, and this channel is stronger in countries with weaker institutions. Both our new database and correlates open important avenues to analyze the sources and effects of profit shifting

     
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    Schriftenreihe: Swiss Finance Institute Research Paper ; No. 22-94
    Schlagworte: Profit shifting; multinational enterprises; nonparametric estimation; intangible assets; institutional quality; global sample
    Umfang: 1 Online-Ressource (78 p)
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    Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments December 1, 2022 erstellt
  5. Nonparametric estimation of sponsored search auctions and impacts of AD quality on search revenue
    Autor*in: Kim, Dongwoo; Pal, Pallavi
    Erschienen: March 2023
    Verlag:  CESifo, Munich, Germany

    This paper presents an empirical model of sponsored search auctions in which advertisers are ranked by bid and ad quality. We introduce a new nonparametric estimator for the advertiser's ad value and its distribution under the 'incomplete... mehr

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    This paper presents an empirical model of sponsored search auctions in which advertisers are ranked by bid and ad quality. We introduce a new nonparametric estimator for the advertiser's ad value and its distribution under the 'incomplete information' assumption. The ad value is characterized by a tractable analytical solution given observed auction parameters. Using Yahoo! search auction data, we estimate value distributions and study the bidding behavior across product categories. We find that advertisers shade their bids more when facing less competition. We also conduct counterfactual analysis to evaluate the impact of score squashing (ad quality raised to power θ < 1) on the auctioneer's revenue. Our results show that product-specific score squashing can enhance auctioneer revenue at the expense of advertiser profit and consumer welfare.

     
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    hdl: 10419/271956
    Schriftenreihe: CESifo working papers ; 10312 (2023)
    Schlagworte: sponsored search links; generalized second price auction; incomplete information; nonparametric estimation; bid shading; score quashing
    Umfang: 1 Online-Ressource (circa 62 Seiten), Illustrationen
  6. Nonparametric estimation of sponsored search auctions and impacts of ad quality on search revenue
    Autor*in: Kim, Dongwoo; Pal, Pallavi
    Erschienen: [2023]
    Verlag:  Cemmap, Centre for Microdata Methods and Practice, The Institute for Fiscal Studies, Department of Economics, UCL, [London]

    This paper presents an empirical model of sponsored search auctions in which advertisers are ranked by bid and ad quality. We introduce a new nonparametric estimator for the advertiser's ad value and its distribution under the 'incomplete... mehr

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    This paper presents an empirical model of sponsored search auctions in which advertisers are ranked by bid and ad quality. We introduce a new nonparametric estimator for the advertiser's ad value and its distribution under the 'incomplete information' assumption. The ad value is characterized by a tractable analytical solution given observed auction parameters. Using Yahoo! search auction data, we estimate value distributions and study the bidding behavior across product categories. We find that advertisers shade their bids more when facing less competition. We also conduct counterfactual analysis to evaluate the impact of score squashing (ad quality raised to power θ < 1) on the auctioneer's revenue. Our results show that product-specific score squashing can enhance auctioneer revenue at the expense of advertiser profit and consumer welfare.

     
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    Weitere Identifier:
    hdl: 10419/284129
    Schriftenreihe: Cemmap working paper ; CWP23, 05
    Schlagworte: Sponsored search links; generalized second price auction; incomplete information; nonparametric estimation; bid shading; score squashing
    Umfang: 1 Online-Ressource (circa 61 Seiten), Illustrationen
  7. Time-varying effects of housing attributes and economic environment on housing price
    Autor*in: Friedrich, Marina; Lin, Yicong; Ramdaras, Pavitram; Telg, Sean; Sluis, Bernhard van der
    Erschienen: [2023]
    Verlag:  Tinbergen Institute, Amsterdam, The Netherlands

    We propose a flexible framework that allows for the relationship between housing prices and their determinants to vary over time. Our model incorporates housing-specific characteristics and macroeconomic variables, while accounting for a gradual... mehr

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    We propose a flexible framework that allows for the relationship between housing prices and their determinants to vary over time. Our model incorporates housing-specific characteristics and macroeconomic variables, while accounting for a gradual global trend that reflects the unobserved external environment. We estimate the trend and coefficient curves by local linear estimation and propose a bootstrap procedure for conducting inference. By employing monthly data from the Dutch housing market, covering 60 municipalities from 2006 to 2020, the proposed models show the capability to accurately describe the comovements of housing prices. Our results show strong statistical evidence of time variation in the effects of housing attributes and macroeconomic variables on prices throughout the entire sample period, revealing that the unemployment rate plays a crucial role between approximately 2012 and 2017. The extracted latent global trend reveals a significant influence of the economic environment and takes the shape of a leading indicator of the property market index. Moreover, we find that both the housing characteristics and the external environment explain comparably high proportions of the variation in housing prices, which stresses the importance of including both components in empirical analyses.

     
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    hdl: 10419/273850
    Schriftenreihe: Array ; TI 2023, 039
    Schlagworte: housing prices; time-varying panels; nonparametric estimation; autoregressive wild bootstrap; simultaneous bands
    Umfang: 1 Online-Ressource (circa 40 Seiten), Illustrationen
  8. Beta-sorted portfolios
    Autor*in: Cattaneo, Matias D.; Crump, Richard K.; Wang, Weining
    Erschienen: [2023]
    Verlag:  Federal Reserve Bank of New York, [New York, NY]

    Beta-sorted portfolios - portfolios comprised of assets with similar covariation to selected risk factors - are a popular tool in empirical finance to analyze models of (conditional) expected returns. Despite their widespread use, little is known of... mehr

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    Beta-sorted portfolios - portfolios comprised of assets with similar covariation to selected risk factors - are a popular tool in empirical finance to analyze models of (conditional) expected returns. Despite their widespread use, little is known of their statistical properties in contrast to comparable procedures such as two-pass regressions. We formally investigate the properties of beta-sorted portfolio returns by casting the procedure as a two-step nonparametric estimator with a nonparametric first step and a beta-adaptive portfolios construction. Our framework rationalizes the well-known estimation algorithm with precise economic and statistical assumptions on the general data generating process. We provide conditions that ensure consistency and asymptotic normality along with new uniform inference procedures allowing for uncertainty quantification and general hypothesis testing for financial applications. We show that the rate of convergence of the estimator is non-uniform and depends on the beta value of interest. We also show that the widely used Fama-MacBeth variance estimator is asymptotically valid but is conservative in general and can be very conservative in empirically relevant settings. We propose a new variance estimator, which is always consistent and provide an empirical implementation which produces valid inference. In our empirical application we introduce a novel risk factor - a measure of the business credit cycle - and show that it is strongly predictive of both the cross-section and time-series behavior of U.S. stock returns.

     
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    hdl: 10419/284028
    Schriftenreihe: Staff reports / Federal Reserve Bank of New York ; no. 1068 (July 2023)
    Schlagworte: beta pricing models; portfolio sorting; nonparametric estimation; partitioning; kernel regression; smoothly varying coefficients
    Umfang: 1 Online-Ressource (circa 103 Seiten), Illustrationen
  9. A mollifier approach to the deconvolution of probability densities
    Autor*in: Maréchal, P.; Simar, Léopold; Vanhems, A.
    Erschienen: [2018]
    Verlag:  Toulouse School of Economics, [Toulouse]

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    Schriftenreihe: Working papers / Toulouse School of Economics ; no 18-965
    Schlagworte: nonparametric estimation; inverse problems; regularization; mollification
    Umfang: 1 Online-Ressource (circa 31 Seiten), Illustrationen
  10. Beta-sorted portfolios
    Autor*in: Cattaneo, Matias D.; Crump, Richard K.; Wang, Weining
    Erschienen: [2023]
    Verlag:  Cemmap, Centre for Microdata Methods and Practice, The Institute for Fiscal Studies, Department of Economics, UCL, [London]

    Beta-sorted portfolios-portfolios comprised of assets with similar covariation to selected risk factors-are a popular tool in empirical finance to analyze models of (conditional) expected returns. Despite their widespread use, little is known of... mehr

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    Beta-sorted portfolios-portfolios comprised of assets with similar covariation to selected risk factors-are a popular tool in empirical finance to analyze models of (conditional) expected returns. Despite their widespread use, little is known of their statistical properties in contrast to comparable procedures such as two-pass regressions. We formally investigate the properties of beta-sorted portfolio returns by casting the procedure as a two-step nonparametric estimator with a nonparametric first step and a beta-adaptive portfolios construction. Our framework rationalizes the well-known estimation algorithm with precise economic and statistical assumptions on the general data generating process. We provide conditions that ensure consistency and asymptotic normality along with new uniform inference procedures allowing for uncertainty quantification and general hypothesis testing for financial applications. We show that the rate of convergence of the estimator is non-uniform and depends on the beta value of interest. We also show that the widely-used Fama-MacBeth variance estimator is asymptotically valid but is conservative in general, and can be very conservative in empirically-relevant settings. We propose a new variance estimator which is always consistent and provide an empirical implementation which produces valid inference. In our empirical application we introduce a novel risk factor - a measure of the business credit cycle - and show that it is strongly predictive of both the cross-section and time-series behavior of U.S. stock returns.

     
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    Weitere Identifier:
    hdl: 10419/284142
    Schriftenreihe: Cemmap working paper ; CWP23, 18
    Schlagworte: Beta pricing models; portfolio sorting; nonparametric estimation; partitioning; kernel regression; smoothly-varying coefficients
    Umfang: 1 Online-Ressource (circa 102 Seiten), Illustrationen
  11. Accounting for individual-specific heterogeneity in intergenerational income mobility
    Autor*in: Chang, Yoosoon; Durlauf, Steven N.; Hu, Bo; Park, Joon Y.
    Erschienen: February 21, 2024
    Verlag:  Australian National University, Crawford School of Public Policy, Canberra

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    Schriftenreihe: CAMA working paper series ; 2024, 18 (February 2024)
    Schlagworte: uncertainty intergenerational income mobility; ordered multinomial probability model; nonparametric estimation; heterogeneous treatment effects; reproducing kernel Hilbert space; effects of parental education
    Umfang: 1 Online-Ressource (circa 32 Seiten), Illustrationen
  12. Model averaging and double machine learning
    Autor*in: Ahrens, Achim; Hansen, Christian Bailey; Schaffer, Mark E.; Wiemann, Thomas
    Erschienen: January 2024
    Verlag:  IZA - Institute of Labor Economics, Bonn, Germany

    This paper discusses pairing double/debiased machine learning (DDML) with stacking, a model averaging method for combining multiple candidate learners, to estimate structural parameters. We introduce two new stacking approaches for DDML:... mehr

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    This paper discusses pairing double/debiased machine learning (DDML) with stacking, a model averaging method for combining multiple candidate learners, to estimate structural parameters. We introduce two new stacking approaches for DDML: short-stacking exploits the cross-fitting step of DDML to substantially reduce the computational burden and pooled stacking enforces common stacking weights over cross-fitting folds. Using calibrated simulation studies and two applications estimating gender gaps in citations and wages, we show that DDML with stacking is more robust to partially unknown functional forms than common alternative approaches based on single pre-selected learners. We provide Stata and R software implementing our proposals.

     
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    Weitere Identifier:
    hdl: 10419/282841
    Schriftenreihe: Discussion paper series / IZA ; no. 16714
    Schlagworte: causal inference; partially linear model; high-dimensional models; super learners; nonparametric estimation
    Umfang: 1 Online-Ressource (circa 54 Seiten), Illustrationen
  13. Nonparametric estimation of natural direct and indirect effects based on inverse probability weighting
    Autor*in: Hsu, Yu-Chin; Huber, Martin; Lai, Tsung-Chih
    Erschienen: 2017-05-01
    Verlag:  University of Fribourg, Switzerland, Faculty of Economics and Social Sciences, Fribourg

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    Schriftenreihe: Working papers SES / Université de Fribourg, Faculté des sciences economiques et sociales ; n. 482 (5.2017)
    Schlagworte: causal mechanisms; direct effects; indirect effects; causal channels; mediation analysis; causal pathways; series logit estimation; nonparametric estimation; inverse probability weighting; propensity score
    Umfang: 1 Online-Ressource (circa 34 Seiten), Illustrationen
  14. Nonparametric estimation of demand elasticities using panel data
    Autor*in: Hoderlein, Stefan; Shum, Matthew
    Erschienen: April 7, 2014
    Verlag:  Boston College, Department of Economics, [Chestnut Hill, Mass.]

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    Schriftenreihe: Working papers / Boston College, Department of Economics ; 891
    Schlagworte: demand elasticities; nonparametric estimation
    Umfang: 1 Online-Ressource (circa 19 Seiten)
  15. Inference on causal effects in a generalized Regression Kink Design
    Erschienen: 2014
    Verlag:  Brandeis Univ., Dep. of Economics, Waltham, Mass.

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    Schriftenreihe: Working paper series / Brandeis University, Department of Economics ; 83
    Schlagworte: Regression discontinuity design; regression kink design; treatment effects; nonseparable models; nonparametric estimation
    Umfang: Online-Ressource (39, [51] S.), graph. Darst.