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Spatial econometrics and the Lasso estimator : theory and applications

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AhrensA_0417_soss.pdf (2.824Mb)
Date
2017-04
Author
Ahrens, Achim
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Abstract
This thesis links two topics of empirical economics: spatial econometrics and the Lasso estimator. Spatial econometrics is concerned with methods and models accounting for interaction effects between units. The Lasso estimator is a regularisation technique that allows for simultaneous variable selection and estimation in a high dimensional setting where the number of parameters may exceed the sample size. Three applied and theoretical articles are presented that demonstrate how spatial econometric research can benefit from high-dimensional methods and, specifically, the Lasso. The introduction in Chapter 1 presents a literature review of both fields and discusses the connections between the two topics. Chapter 2 examines the effect of economic growth on civil conflicts in Africa. The Lasso estimator is employed to generate instrumental variables, which account for non-linearity and spatial heterogeneity. The theoretical contribution in Chapter 3 proposes a two-step Lasso estimator that can consistently estimate the spatial weights matrix in a spatial autoregressive panel model. Chapter 4 is an application to the US housing market. A Lasso-based estimation method is considered that controls for spatial effects in a spatial error-correction model. Chapter 5 provides concluding remarks.
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http://hdl.handle.net/10399/3416
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©Heriot-Watt University, Edinburgh, Scotland, UK EH14 4AS.

Maintained by the Library
Tel: +44 (0)131 451 3577
Library Email: libhelp@hw.ac.uk
ROS Email: open.access@hw.ac.uk

Scottish registered charity number: SC000278

  • About
  • Copyright
  • Accessibility
  • Policies
  • Privacy & Cookies
  • Feedback
AboutCopyright
AccessibilityPolicies
Privacy & Cookies
Feedback