
We estimate output gaps using three methods for Mainland China on annual data spanning 1982-2003. The estimates are similar and appear to co-move with inflation. Standard Phillips curves, however, do not fit the data well. This may reflect the omission of some important variable(s) such as the effect of price deregulation, trade liberalisation and/or changes in the exchange rate regime. We re-estimate the Phillips curves assuming that there is an unobserved variable that follows an AR(2) process. The modified model fits the data much better and accounts for some of the surprising features of the simple Phillips curve estimates.
output gap, omitted variables, Phillips curve, China, output gap, Phillips curve, China, omitted variab les, jel: jel:E40, jel: jel:E30, jel: jel:C22, jel: jel:E53
output gap, omitted variables, Phillips curve, China, output gap, Phillips curve, China, omitted variab les, jel: jel:E40, jel: jel:E30, jel: jel:C22, jel: jel:E53
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 30 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
