On cointegration between the insurance market and economic activity
(2020) In Empirical Economics 59(3). p.1127-1138- Abstract
Recent literature mainly examines the causal relationship between the insurance market and economic activity, while agreeing on presence of cointegration. The bulk of this evidence relies on Pedroni’s (Econom Theory 20(03):597–625, 2004) very popular residual-based panel cointegration test. However, this test not only requires that the number of time periods is large, but also that it is large relative to the number of cross section units. In this paper, we demonstrate that violating this requirement leads to Pedroni’s test over-rejecting the null hypothesis of no cointegration. We then re-investigate cointegration between insurance market activity and real output using a dataset covering 49 countries over 36 years. While Pedroni’s test... (More)
Recent literature mainly examines the causal relationship between the insurance market and economic activity, while agreeing on presence of cointegration. The bulk of this evidence relies on Pedroni’s (Econom Theory 20(03):597–625, 2004) very popular residual-based panel cointegration test. However, this test not only requires that the number of time periods is large, but also that it is large relative to the number of cross section units. In this paper, we demonstrate that violating this requirement leads to Pedroni’s test over-rejecting the null hypothesis of no cointegration. We then re-investigate cointegration between insurance market activity and real output using a dataset covering 49 countries over 36 years. While Pedroni’s test rejects the null, using a more suitable test procedure yields no evidence of cointegration. This suggests that much of the earlier evidence should be re-evaluated. Equally important, if the evidence on cointegration is misleading, then subsequent causality results are also likely to be misleading.
(Less)
- author
- Petrova, Yana LU
- organization
- publishing date
- 2020-09
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Cointegration, Economic activity, Insurance, Non-stationary panel data
- in
- Empirical Economics
- volume
- 59
- issue
- 3
- pages
- 12 pages
- publisher
- Physica Verlag
- external identifiers
-
- scopus:85064170166
- ISSN
- 0377-7332
- DOI
- 10.1007/s00181-019-01669-6
- language
- English
- LU publication?
- yes
- id
- f8901dd1-14cd-487e-bab4-5e8c7232d7eb
- date added to LUP
- 2019-05-02 15:11:30
- date last changed
- 2022-04-25 22:51:19
@article{f8901dd1-14cd-487e-bab4-5e8c7232d7eb,
abstract = {{<p>Recent literature mainly examines the causal relationship between the insurance market and economic activity, while agreeing on presence of cointegration. The bulk of this evidence relies on Pedroni’s (Econom Theory 20(03):597–625, 2004) very popular residual-based panel cointegration test. However, this test not only requires that the number of time periods is large, but also that it is large relative to the number of cross section units. In this paper, we demonstrate that violating this requirement leads to Pedroni’s test over-rejecting the null hypothesis of no cointegration. We then re-investigate cointegration between insurance market activity and real output using a dataset covering 49 countries over 36 years. While Pedroni’s test rejects the null, using a more suitable test procedure yields no evidence of cointegration. This suggests that much of the earlier evidence should be re-evaluated. Equally important, if the evidence on cointegration is misleading, then subsequent causality results are also likely to be misleading.</p>}},
author = {{Petrova, Yana}},
issn = {{0377-7332}},
keywords = {{Cointegration; Economic activity; Insurance; Non-stationary panel data}},
language = {{eng}},
number = {{3}},
pages = {{1127--1138}},
publisher = {{Physica Verlag}},
series = {{Empirical Economics}},
title = {{On cointegration between the insurance market and economic activity}},
url = {{http://dx.doi.org/10.1007/s00181-019-01669-6}},
doi = {{10.1007/s00181-019-01669-6}},
volume = {{59}},
year = {{2020}},
}