| 1. |
- Alheety, M. I., et al.
(författare)
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A new kind of stochastic restricted biased estimator for logistic regression model
- 2021
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Ingår i: Journal of Applied Statistics. - : Taylor & Francis. - 0266-4763 .- 1360-0532. ; 48:9, s. 1559-1578
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Tidskriftsartikel (refereegranskat)abstract
- In the logistic regression model, the variance of the maximum likelihood estimator is inflated and unstable when the multicollinearity exists in the data. There are several methods available in literature to overcome this problem. We propose a new stochastic restricted biased estimator. We study the statistical properties of the proposed estimator and compare its performance with some existing estimators in the sense of scalar mean squared criterion. An example and a simulation study are provided to illustrate the performance of the proposed estimator.
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| 2. |
- Alheety, Mustafa I., et al.
(författare)
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Modifed almost unbiased two-parameter estimator for the Poisson regression model with an application to accident data
- 2021
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Ingår i: SORT - Statistics and Operations Research Transactions. - : INST ESTADISTICA CATALUNYA-IDESCAT. - 1696-2281 .- 2013-8830. ; 45:2, s. 121-142
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Tidskriftsartikel (refereegranskat)abstract
- Due to the large amount of accidents negatively affecting the wellbeing of the survivors and their families, a substantial amount of research is conducted to determine the causes of road accidents. This type of data come in the form of non-negative integers and may be modelled using the Poisson regression model. Unfortunately, the commonly used maximum likelihood estimator is unstable when the explanatory variables of the Poisson regression model are highly correlated. Therefore, this paper proposes a new almost unbiased estimator which reduces the instability of the maximum likelihood estimator and at the same time produce smaller mean squared error. We study the sta-tistical properties of the proposed estimator and a simulation study has been conducted to compare the performance of the estimators in the smaller mean squared error sense. Finally, Swedish traffic fatality data are analyzed to show the beneft of the proposed method.
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| 3. |
- Ali, Abdul Aziz, 1966-, et al.
(författare)
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A wavelet-based variance ratio unit root test for a system of equations
- 2020
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Ingår i: Studies in Nonlinear Dynamics and Econometrics. - : Walter de Gruyter. - 1081-1826 .- 1558-3708. ; 24:3, s. 1-16
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we suggest a unit root test for a system of equations using a spectral variance decomposition method based on the Maximal Overlap Discrete Wavelet Transform. We obtain the limiting distribution of the test statistic and study its small sample properties using Monte Carlo simulations. We find that, for multiple time series of small lengths, the wavelet-based method is robust to size distortions in the presence of cross-sectional dependence. The wavelet-based test is also more powerful than the Cross-sectionally Augmented Im et al. unit root test (Pesaran, M. H. 2007. "A Simple Panel Unit Root Test in the Presence of Cross-section Dependence." Journal of Applied Econometrics 22 (2): 265-312.) for time series with between 20 and 100 observations, using systems of 5 and 10 equations. We demonstrate the usefulness of the test through an application on evaluating the Purchasing Power Parity theory for the Group of 7 countries and find support for the theory, whereas the test by Pesaran (Pesaran, M. H. 2007. "A Simple Panel Unit Root Test in the Presence of Cross-section Dependence." Journal of Applied Econometrics 22 (2): 265-312.) finds no such support. © 2019 Walter de Gruyter GmbH, Berlin/Boston.
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| 4. |
- Almasri, Abdullah, 1965-, et al.
(författare)
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A wavelet-based panel unit-root test in the presence of an unknown structural break and cross-sectional dependency, with an application of purchasing power parity theory in developing countries
- 2017
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Ingår i: Applied Economics. - : Taylor & Francis. - 0003-6846 .- 1466-4283. ; 49:21, s. 2096-2105
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Tidskriftsartikel (refereegranskat)abstract
- This article introduces two different non-parametric wavelet-based panel unit-root tests in the presence of unknown structural breaks and cross-sectional dependencies in the data. These tests are compared with a previously suggested non-parametric wavelet test, the parameteric Im-Pesaran and Shin (IPS) test and a Wald type of test. The results from the Monte Carlo simulations clearly show that the new wavelet-ratio tests are superior to the traditional tests both in terms of size and power in panel unit-root tests because of its robustness to cross-section dependency and structural breaks. Based on an empirical Central American panel application, we can, in contrast to previous research (where bias due to structural breaks is simply disregarded), find strong, clear-cut support for purchasing power parity (PPP) in this developing region.
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| 5. |
- Duras, Toni, et al.
(författare)
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Using machine learning to select variables in data envelopment analysis : Simulations and application using electricity distribution data
- 2023
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Ingår i: Energy Economics. - : Elsevier. - 0140-9883 .- 1873-6181. ; 120
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Tidskriftsartikel (refereegranskat)abstract
- Agencies that regulate electricity providers often apply nonparametric data envelopment analysis (DEA) to assess the relative efficiency of each firm. The reliability and validity of DEA are contingent upon selecting relevant input variables. In the era of big (wide) data, the assumptions of traditional variable selection techniques are often violated due to challenges related to high-dimensional data and their standard empirical properties. Currently, regulators have access to a large number of potential input variables. Therefore, our aim is to introduce new machine learning methods for regulators of the energy market. We also propose a new two-step analytical approach where, in the first step, the machine learning-based adaptive least absolute shrinkage and selection operator (ALASSO) is used to select variables and, in the second step, selected variables are used in a DEA model. In contrast to previous research, we find, by using a more realistic data-generating process common for production functions (i.e., Cobb–Douglas and Translog), that the performance of different machine learning techniques differs substantially in different empirically relevant situations. Simulations also reveal that the ALASSO is superior to other machine learning and regression-based methods when the collinearity is low or moderate. However, in situations of multicollinearity, the LASSO approach exhibits the best performance. We also use real data from the Swedish electricity distribution market to illustrate the empirical relevance of selecting the most appropriate variable selection method.
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| 6. |
- Habimana, Olivier, et al.
(författare)
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A wavelet-based approach for Johansen’s likelihood ratio test for cointegration in the presence of measurement errors : An application to CO2 emissions and real GDP data
- 2021
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Ingår i: Communications in Statistics Case Studies Data Analysis and Applications. - : Taylor & Francis. - 2373-7484. ; 7:2, s. 128-145
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Tidskriftsartikel (refereegranskat)abstract
- We suggest a wavelet filtering technique as a remedy to the problem of measurement errors when testing for cointegration using Johansen’s (1988) likelihood ratio test. Measurement errors, which more or less are always present in empirical economic data, essentially indicates that the variable of interest (the true signal) is contaminated with noise, which may induce biased and inconsistent estimates and erroneous inference. Our Monte Carlo experiments demonstrate that measurement errors distort the statistical size of Johansen’s cointegration test in finite samples; the test is significantly oversized. A contribution and major finding of this article is that the proposed wavelet-based technique significantly improves the statistical size of the traditional Johansen test in small and medium sized samples. Since Johansen’s test is a standard cointegration test, and we demonstrate that the constantly present measurement errors in empirical data over sizes the test, this simple alteration can be used in most situations with more reliable finite sample inference. We empirically examine the long-run relation between CO2 emissions and the real GDP in the G7 countries. The traditional Johansen tests provide evidence of an equilibrium relation for Canada and weak evidence for the US. However, the suggested size-unbiased wavelet-filtering approach consistently indicates no evidence of cointegration for all six countries.
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| 7. |
- Habimana, Olivier, et al.
(författare)
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Testing for nonlinear unit roots in the presence of a structural break with an application to the qualified PPP during the 1997 Asian financial crisis
- 2018
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Ingår i: International journal of finance and economics. - : John Wiley & Sons. - 1076-9307 .- 1099-1158. ; 23:3, s. 221-232
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Tidskriftsartikel (refereegranskat)abstract
- This paper applies Monte Carlo simulations to evaluate the size and power properties in the presence of a structural break, for the standard Augmented Dickey-Fuller (ADF) test versus nonlinear exponential smooth transition autoregressive unit root tests. The break causes the tests to be undersized, and the statistical power considerably decreases. Moreover, the effect is intensified in small samples and very much increased for more persistent nonlinear series. As a remedy, we modify the standard ADF and exponential smooth transition autoregressive unit root tests in order to adjust for a structural break. This improves both the power and the size considerably, even though the empirical size still is lower than the nominal one. More persistent series are more affected by structural breaks, and the new tests are most powerful under the existence of a rather persistent nonlinear data generating process (which is an empirically relevant and common type of data generating process). The proposed tests are applied to investigate mean reversion in the real effective exchange rates of 5 East and Southeast Asian countries, taking into account the structural change in exchange rate regime brought about by the 1997 Asian financial crisis. The empirical findings corroborate our simulation results; the modified more powerful tests are able to reject the unit root in all 5 countries, whereas the tests that do not consider the structural break could only reject in one of these cases.
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| 8. |
- Hacker, R. Scott, et al.
(författare)
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An investigation of the causal relations between exchange rates and interest rate differentials using wavelets
- 2014
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Ingår i: International Review of Economics and Finance. - : Elsevier BV. - 1059-0560 .- 1873-8036. ; 29, s. 321-329
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Tidskriftsartikel (refereegranskat)abstract
- This paper uses wavelet analysis to investigate causality between the spot exchange rate and the nominal interest rate differential for seven country pairs, which includes Sweden. Impulse response functions are also utilized to examine the signs of how one of these variables affects the other over time. One key empirical finding from the causality tests is that there is strengthening evidence of the nominal interest rate differential Granger causing the exchange rate as the wavelet time scale increases. When considering impulse responses on how the interest rate differential affects the exchange rate, there appears to be some evidence of more negative relationships at the shorter time scales (i.e. an increase in the Swedish interest rate compared to that of another country is associated with a lower Swedish krona price of the other country's currency) and more positive relationships at the longer time scales.
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| 9. |
- Hacker, R. Scott, et al.
(författare)
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The relationship between exchange rates and interest rate differentials : A wavelet approach
- 2012
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Ingår i: The World Economy. - : Wiley. - 0378-5920 .- 1467-9701. ; 35:9, s. 1162-1185
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Tidskriftsartikel (refereegranskat)abstract
- This paper uses wavelet analysis to investigate the relationship between the spot exchange rate and interest rate differential for seven pairs of countries, with a small country, Sweden, included in each case. The key empirical results show that there tends to be a negative relationship between the spot exchange rate (domestic-currency price of foreign currency) and the nominal interest rate differential (approximately the domestic interest rate minus the foreign interest rate) at the shortest time scales, while a positive relationship is shown at the longest time scales. This indicates that among models of exchange rate determination using the asset approach, the sticky-price models are supported in the short-run and flexible-price models in the long-run.
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| 10. |
- Holgersson, Thomas, et al.
(författare)
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Testing for Panel Unit Roots under General Cross-sectional Dependence
- 2016
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Ingår i: Communications in Statistics-Simulation and Computation. - : Informa UK Limited. - 0361-0918 .- 1532-4141. ; 45:5, s. 1785-1801
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Tidskriftsartikel (refereegranskat)abstract
- In this article, we generalize four tests of multivariate linear hypothesis to panel data unit root testing. The test statistics are invariant to certain linear transformations of data and therefore simulated critical values may conveniently be used. It is demonstrated that all four tests remains well behaved in cases of where there are heterogeneous alternatives and cross-correlations between marginal variables. A Monte Carlo simulation is included to compare and contrast the tests with two well-established ones.
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