Yiannis Karavias

Yiannis Karavias
University of Birmingham · Department of Economics

PhD

About

27
Publications
5,724
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202
Citations
Introduction
I am an Assistant Professor at the department of Economics in the University of Birmingham. My research area is econometrics, in particular panel data econometrics and their applications in economic growth, banking, and corporate finance. Methodological interests include panel data models, structural breaks, threshold regression and nonstationarity.
Additional affiliations
September 2015 - present
University of Birmingham
Position
  • Professor (Assistant)
September 2012 - August 2015
University of Nottingham
Position
  • PostDoc Position

Publications

Publications (27)
Preprint
Full-text available
Identifying structural change is a crucial step in analysis of time series and panel data. The longer the time span, the higher the likelihood that the model parameters have changed as a result of major disruptive events, such as the 2007--2008 financial crisis and the 2020 COVID--19 outbreak. Detecting the existence of breaks, and dating them is t...
Preprint
Full-text available
This article introduces the xtbunitroot command in Stata, which implements the panel data unit root tests developed by Karavias and Tzavalis (2014). These tests allow for one or two structural breaks in deterministic components of the series and can be seen as panel data counterparts of the tests by Zivot and Andrews (1992) and Lumsdaine and Papell...
Article
Full-text available
Missing data or missing values are a common phenomenon in applied panel data research and of great interest for panel data unit root testing. The standard approach in the literature is to balance the panel by removing units and/or trimming a common time period for all units. However, this approach can be costly in terms of lost information. Instead...
Preprint
Full-text available
Dealing with structural breaks is an important step in most, if not all, empirical economic research. This is particularly true in panel data comprised of many cross-sectional units, such as individuals, firms or countries, which are all affected by major events. The COVID-19 pandemic has affected most sectors of the global economy, and there is by...
Code
xtbunitroot performs panel unit root tests allowing for structural breaks, using the methodology developed by Karavias and Tzavalis (2014). These tests allow for one or two structural breaks in the deterministic components of the series and can be used in both fixed-T and large-T settings, where T is the number of time series observations in the sa...
Article
Full-text available
We investigate the existence of evidence of investor sentiment on share price deviations from their intrinsic values across two sentiment regimes of shares market: the low-to-normal and the excess one. We use the residual income valuation model to calculate the intrinsic values of shares based on accounting fundamentals and we suggest a panel data...
Article
Full-text available
This paper develops a new method for testing for Granger non-causality in panel data models with large cross-sectional (N) and time series (T) dimensions. The method is valid in models with homogeneous or heterogeneous coefficients. The novelty of the proposed approach lies in the fact that under the null hypothesis, the Granger-causation parameter...
Article
The power of Granger non-causality tests in panel data depends on the type of the alternative hypothesis: feedback from other variables might be homogeneous, homogeneous within groups or heterogeneous across different panel units. Existing tests have power against only one of these alternatives and may fail to reject the null hypothesis if the spec...
Article
Panel data unit root tests, which can be applied to data that do not have many time series observations, are based on very restrictive error and deterministic component specification assumptions. In this paper, we develop a new, doubly modified estimator, based on which we propose a panel unit root test that allows for multiple structural breaks, l...
Article
Full-text available
We derive a stochastic expansion of the error variance-covariance matrix estimator for the linear regression model under Gaussian AR(1) errors. The higher order accuracy terms of the re…ned formula are not directly derived from formal Edgeworth-type expansions but instead, the paper adopts Magadalinos' (1992) stochastic order of ! which is a conven...
Preprint
This paper examines the impact of net trade credit on firm performance. The analysis is carried out by using a novel nonlinear threshold model and a large panel of European firms over the period 2003-2015. We uncover a nonmonotonic relationship between net trade credit and firm performance. This relationship is characterized by two regimes: when ne...
Article
The asymptotic local power of least squares based fi…xed-T panel unit root tests allowing for a structural break in their individual effects and/or incidental trends of the AR(1) panel data model is studied. Limiting distributions of these tests are derived under a sequence of local alternatives and analytic expressions show how their means and var...
Article
Full-text available
We examine the nature of the relationship between government size and economic growth and identify the optimal level of government size using a large dataset through a novel and very general non-linear panel Generalized Method of Moments approach. We show that this relationship is statistically signi…cant above and below the optimal level, even aft...
Article
Full-text available
We study the convergence properties of inflation rates among the countries of the European Monetary Union over the period 1980–2013. Recently developed panel unit root/stationarity tests cannot reject the stationarity hypothesis. This implies that some countries have been in the process of converging absolutely or relatively. By using a clustering...
Article
Full-text available
Refined asymptotic methods are used to produce degrees-of-freedom- adjusted Edgeworth and Cornish-Fisher size corrections of the t and F testing procedures for the parameters of a S.U.R. model with serially correlated errors. The corrected tests follow the Student-t and F distributions, respectively, with an approximation error of order Oτ3, where...
Article
Full-text available
The asymptotic local power properties of various fixed T panel unit root tests with serially correlated errors and incidental trends are studied. Asymptotic (over N) local power functions are analytically derived and through them the effects of general forms of serial correlation are examined. Comparing these we find that a test based on an instrum...
Article
Full-text available
This paper investigates at what extent deviations between market share prices and their fundamental values can be explained by risk premium and/or investors’ sentiment effects. This is done based on recent panel data econometric techniques controlling for the effects of unobserved common factors on our estimation and inference procedures. To calcul...
Research
Full-text available
This paper examines the nature of the relationship between government size and economic growth and identifies the optimal level of government size through a novel and very general non-linear panel GMM.
Research
Full-text available
This paper examines the nature of the relationship between government size and economic growth and identifies the optimal level of government size through a novel and very general non-linear panel GMM approach.
Article
Full-text available
Standard banking theory suggests that there exists an optimal level of credit risk that yields maximum bank profit. We identify the optimal level of risk-weighted assets that maximizes banks’ returns in the full sample of US banks over the period 1996–2011. We find that this optimal level is cyclical, being higher than the realized credit risk in r...
Article
Full-text available
Panel data unit root tests which allow for a common structural break in the individual effects or linear trends of the AR(1) panel data model are suggested. These allow the date of the break to be unknown. The tests assume that the time-dimension of the panel (TT) is fixed (finite) while the cross-section (NN) is large. Under the null hypothesis of...
Article
Full-text available
We extend Breitung’s (2000) panel data unit root test to the case of fixed time (TT) dimension while still allowing for heteroscedastic and serially correlated error terms. The analytic local power function of the new test is derived assuming that only the cross section dimension of the panel grows large. It is found that, if the errors are seriall...