On the Estimation and Inference of a Cointegrated Regression in Panel Data

Kao, Chihwa; Chiang, Min-Hsien

doi:10.2139/ssrn.2379

Cited by 136 publications

(76 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The panel unit root tests have further been extended to various panel tests for cointegration by, e.g. Pedroni (1996), Kao (1999), Kao and Chiang (2000) and McCoskey and Kao (1997). These panel cointegration tests are in essence univariate extensions of the original panel unit root tests based on the residuals from a first-step cointegrating regression in the spirit of the two-step cointegration test approach by Engle and Granger (1987).…”

Section: Introductionmentioning

confidence: 99%

Likelihood‐based cointegration tests in heterogeneous panels

Larsson

Lyhagen

Löthgren

2001

The Econometrics Journal

418

317

View full text Add to dashboard Cite

This paper presents a maximum likelihood panel test of the cointegrating rank in heterogeneous panel models based on the mean of the individual rank trace statistics. The existence of the first two moments of the asymptotic distribution of the individual trace statistic is established. Based on this, the asymptotic distribution of the test statistic is shown to be normal. The small-sample size and power properties are investigated using Monte Carlo simulations. An empirical example for a consumption model including consumption, income and inflation is estimated for 23 OECD countries over the period 1960-1994. The results indicate that two cointegrating relations exist in the system: one containing consumption and income and one inflation only.

show abstract

Section: Introductionmentioning

confidence: 99%

Likelihood‐based cointegration tests in heterogeneous panels

Larsson

Lyhagen

Löthgren

2001

The Econometrics Journal

418

317

View full text Add to dashboard Cite

show abstract

“…Reference [47] note that a linear combination of two or more I(1) series may be cointegrated, and such linear combination yields a long-run relationship between the variables. References [42]- [44] [50] suggested the use Fully Modified OLS (FMOLS) to provide optimal estimates of cointegrating regressions. The method modifies least squares to account for serial correlation effects and for the endogeneity in the regressors that result from the existence of a cointegrating relationship.…”

Section: Inferential Analysismentioning

confidence: 99%

An Empirical Investigation into the Effect of Enhancing Airline Capacity on Load Factor: A Case of Kenya’s Low-Cost Carriers

Aomo¹,

Oima²,

Oginda³

2016

AJIBM

View full text Add to dashboard Cite

This paper reports the findings of an empirical study on the low-cost airline market. A lot of literatures on low-cost carriers' business model agree that low-cost airlines operate with high load factors. However, due to variations in the market development life cycle of low-cost carriers from one region to another, empirical evidences have shown mixed results of the effect of increasing airline capacity on load factor. The paper therefore extends this analysis by examining two airlines in Kenya over 72 months period; and explores such impact using panel data to capture both time-series and cross-sectional elements over the period. Findings indicate that fleet capacity is a significant positive predictor of load factor. The paper finally underlines that increasing capacity by 1 seat will result in an increase of 0.03% in load factor.

show abstract

“…Another example is the panel cointegration process (e.g., Phillips and Moon (1999), Kao and Chiang (2000)):…”

Section: Asymptotic Distributionmentioning

confidence: 99%

“…This is in contrast to Durbin and Watson (1951) and Box and Pierce (1970), whose test statistics or limit distributions have to be modified when applied to estimated residuals of a stationary dynamic model. If regressors contain deterministic or stochastic trending variables, the limit distributions of these tests will become nonstandard (e.g., Kao and Chiang (2000), Kao and Emerson (2004)). Intuitively, parameter estimation uncertainty for β induces an adjustment of a finite number of degrees of freedom forŴ 1 andŴ 2 , but this becomes negligible as n → ∞…”

Section: Asymptotic Distributionmentioning

confidence: 99%

Wavelet-Based Testing for Serial Correlation of Unknown Form in Panel Models

Hong¹,

Kao²

2004

Econometrica

View full text Add to dashboard Cite

Wavelet analysis is a new mathematical method developed as a unified field of science over the last decade or so. As a spatially adaptive analytic tool, wavelets are useful for capturing serial correlation where the spectrum has peaks or kinks, as can arise from persistent dependence, seasonality, and other kinds of periodicity. This paper proposes a new class of generally applicable wavelet‐based tests for serial correlation of unknown form in the estimated residuals of a panel regression model, where error components can be one‐way or two‐way, individual and time effects can be fixed or random, and regressors may contain lagged dependent variables or deterministic/stochastic trending variables. Our tests are applicable to unbalanced heterogenous panel data. They have a convenient null limit N(0,1) distribution. No formulation of an alternative model is required, and our tests are consistent against serial correlation of unknown form even in the presence of substantial inhomogeneity in serial correlation across individuals. This is in contrast to existing serial correlation tests for panel models, which ignore inhomogeneity in serial correlation across individuals by assuming a common alternative, and thus have no power against the alternatives where the average of serial correlations among individuals is close to zero. We propose and justify a data‐driven method to choose the smoothing parameter—the finest scale in wavelet spectral estimation, making the tests completely operational in practice. The data‐driven finest scale automatically converges to zero under the null hypothesis of no serial correlation and diverges to infinity as the sample size increases under the alternative, ensuring the consistency of our tests. Simulation shows that our tests perform well in small and finite samples relative to some existing tests.

show abstract

On the Estimation and Inference of a Cointegrated Regression in Panel Data

Cited by 136 publications

References 12 publications

Likelihood‐based cointegration tests in heterogeneous panels

Likelihood‐based cointegration tests in heterogeneous panels

An Empirical Investigation into the Effect of Enhancing Airline Capacity on Load Factor: A Case of Kenya’s Low-Cost Carriers

Wavelet-Based Testing for Serial Correlation of Unknown Form in Panel Models

Contact Info

Product

Resources

About