Publikation: Working paper › Forskning

- Rp09 17
Forlagets udgivne version, 269 KB, PDF-dokument

- Institut for Økonomi

I comment on the controversy between McCloskey & Ziliak and

Hoover & Siegler on statistical versus economic significance, in

the March 2008 issue of the Journal of Economic Methodology.

I argue that while McCloskey & Ziliak are right in emphasizing

'real error', i.e. non-sampling error that cannot be eliminated

through specification testing, they fail to acknowledge those areas

in economics, e.g. rational expectations macroeconomics and

asset pricing, where researchers clearly distinguish between statistical

and economic significance and where statistical testing

plays a relatively minor role in model evaluation. In these areas

models are treated as inherently misspecified and, consequently,

are evaluated empirically by other methods than statistical tests.

I also criticise McCloskey & Ziliak for their strong focus on the

size of parameter estimates while neglecting the important question

of how to obtain reliable estimates, and I argue that significance

tests are useful tools in those cases where a statistical

model serves as input in the quantification of an economic model.

Finally, I provide a specific example from economics - asset return

predictability - where the distinction between statistical and

economic significance is well appreciated, but which also shows

how statistical tests have contributed to our substantive economic

understanding.

Hoover & Siegler on statistical versus economic significance, in

the March 2008 issue of the Journal of Economic Methodology.

I argue that while McCloskey & Ziliak are right in emphasizing

'real error', i.e. non-sampling error that cannot be eliminated

through specification testing, they fail to acknowledge those areas

in economics, e.g. rational expectations macroeconomics and

asset pricing, where researchers clearly distinguish between statistical

and economic significance and where statistical testing

plays a relatively minor role in model evaluation. In these areas

models are treated as inherently misspecified and, consequently,

are evaluated empirically by other methods than statistical tests.

I also criticise McCloskey & Ziliak for their strong focus on the

size of parameter estimates while neglecting the important question

of how to obtain reliable estimates, and I argue that significance

tests are useful tools in those cases where a statistical

model serves as input in the quantification of an economic model.

Finally, I provide a specific example from economics - asset return

predictability - where the distinction between statistical and

economic significance is well appreciated, but which also shows

how statistical tests have contributed to our substantive economic

understanding.

Originalsprog | Engelsk |
---|---|

Udgivelsessted | Aarhus |

Udgiver | Institut for Økonomi, Aarhus Universitet |

Antal sider | 24 |

Status | Udgivet - 2009 |

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