Predicting U.S. Recessions with Dynamic Binary Response Models
Bibliographic Data
| ID | 19317817 |
|---|---|
| Authors | Heikki Kauppi (0000-0002-4115-102X, University of Turku), Pentti Saikkonen (University of Helsinki) |
| Year | 2008 |
| Volume | 90 |
| Issue | 4 |
| Pages | 777-791 |
| Publication date | 2008-11-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | The Review of Economics and Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0034-6535 • E-ISSN: 1530-9142 |
| Publisher | MIT Press - Journals (PUBLISHER) |
| DOI | 10.1162/rest.90.4.777 |
| OpenAlex | W2118229469 |
| Language | EN |
| Citations received | 14 |
| References cited | 12 |
We develop dynamic binary probit models and apply them for predicting U.S. recessions using the interest rate spread as the driving predictor. The new models use lags of the binary response (a recession dummy) to forecast its future values and allow for the potential forecast power of lags of the underlying conditional probability. We show how multiperiod-ahead forecasts are computed iteratively using the same one-period-ahead model. Iterated forecasts that apply specific lags supported by statistical model selection procedures turn out to be more accurate than previously used direct forecasts based on horizon-specific model specifications
Binary number · Consensus forecast · Econometrics · Economics · Iterated function · Keynesian economics · Model selection · Probit model · Recession · Statistics · Computer Science · Financial Risk and Volatility Modeling · Global Financial Crisis and Policies · Mathematics · Monetary Policy and Economic Impact
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Modelling of Economic and Financial Conditions for Real‐Time Prediction of Recessions
Has the Recession Started
A systematic literature review on business cycle approaches
An Econometric Analysis of Some Models for Constructed Binary Time Series
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Les variables financières sont-elles utiles pour anticiper la croissance économique
Unveiling how financial markets could intensify climate change risks
A Fast Estimator for Binary Choice Models with Spatial, Temporal, and Spatio-Temporal Interdependence
Information Theory and an Extension of the Maximum Likelihood Principle
Estimating the Dimension of a Model
A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
A New Measure of Fit for Equations With Dichotomous Dependent Variables
Dynamic Forecasts of Qualitative Variables
Predicting U.S. Recessions
| Unique citing works | 14 |
|---|---|
| Citations per year | 0.88 |
| Citation span | 2010 - 2026 (17) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 14 |