Niko Hauzenberger, Florian Huber
arXiv 21 Nov 2018 · Econometrics · publishedJournal of Forecasting (2019) · 8 citations (OpenAlex)
arXiv:1811.08818 · PDF · DOI · OpenAlex · Extracted main text
In this paper we aim to improve existing empirical exchange rate models by accounting for uncertainty with respect to the underlying structural representation. Within a flexible Bayesian non-linear time series framework, our modeling approach assumes that different regimes are characterized by commonly used structural exchange rate models, with their evolution being driven by a Markov process. We assume a time-varying transition probability matrix with transition probabilities depending on a measure of the monetary policy stance of the central bank at the home and foreign country. We apply this model to a set of eight exchange rates against the US dollar. In a forecasting exercise, we show that model evidence varies over time and a model approach that takes this empirical evidence seriously yields improvements in accuracy of density forecasts for most currency pairs considered.
appendix boundary found by appendix_command · 95% of the source is main text. Read the extracted text to check this.
The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Molodtsova T and Papell DH (2009) Out-of-sample exchange rate predic… Journal of International Economics 77(2), 167–180 | 0.928 | 4 | 3 | 100% |
| 2 | Kaufmann S (2015) K-state switching models with time-varying transit… Journal of Econometrics 187(1), 82–94 | 0.874 | 7 | 2 | 100% |
| 3 | Amisano G and Fagan G (2013) Money growth and inflation: a regime sw… Journal of International Money and Finance 33, 118–145 | 0.874 | 5 | 2 | 100% |
| 4 | Byrne JP, Korobilis D and Ribeiro PJ (2016) Exchange rate predictabi… Journal of International Money and Finance 62(1), 1–24 | 0.874 | 5 | 2 | 100% |
| 5 | Wright JH (2008) Bayesian model averaging and exchange rate forecasts Journal of Econometrics 146(2), 329–341 | 0.843 | 3 | 3 | 100% |
| 6 | Beckmann J, Koop G, Korobilis D and Schüssler R (2018) Exchange rate… Essex Finance Centre Working Papers | 0.737 | 3 | 2 | 100% |
| 7 | Frühwirth-Schnatter S (2006) Finite mixture and Markov switching mod… Springer Science & Business Media | 0.644 | 3 | 2 | 67% |
| 8 | Engel C and West KD (2006) Taylor rules and the Deutschmark-Dollar r… Journal of Money, Credit and Banking 38(5), 1175–1194 | 0.644 | 2 | 2 | 100% |
| 9 | Beckmann J and Schüssler R (2016) Forecasting exchange rates under p… Journal of International Money and Finance 60, 267–288 | 0.644 | 2 | 2 | 100% |
| 10 | Byrne JP, Korobilis D and Ribeiro PJ (2018) On the sources of uncert… International Economic Review 59(1), 329–357 | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 48 scored citations.