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Author:Boldin, Michael D. 

Report
An efficient, three-step algorithm for estimating error-correction models with an application to the U.S. macroeconomy

This paper describes a three-step algorithm for estimating a system of error-correction equations that can be easily programmed using least-squares procedures. Nonetheless, the algorithm is both statistically and computationally efficient and when iterated gives maximum likelihood estimates of cointegration effects. Most important, the algorithm can handle different levels of cointegration, over-identified systems, breaks in trend, and complicated specifications for the short-run dynamics. The procedure is demonstrated with some small macroeconometric models, which suggest that breaks in the ...
Staff Reports , Paper 6

Report
An evaluation of methods for determining turning points in the business cycle

Research Paper , Paper 9303

Monograph
The credit crunch and the construction industry

Monograph

Report
Using switching models to study business cycle asymmetries: 1. overview of methodology and application

Switching Models are advocated as interesting and tractable alternatives to conventional, linear models of the business cycle. Applications are motivated by the belief that expansions and recessions are distinct regimes with different data generating processes. Therefore, it is important that econometric specifications capture this fundamental asymmetry. With Switching Models, both the time-periods and characteristics of business cycle regimes can be derived simultaneously. Asymmetries can then be tested with a minimum of prior modeling assumptions and restrictions. Results with monthly data ...
Research Paper , Paper 9211

Working Paper
Weather-adjusting employment data

First version: December 18, 2014. This version: January 12, 2015. This paper proposes and implements a statistical methodology for adjusting employment data for the effects of deviation in weather from seasonal norms. This is distinct from seasonal adjustment, which only controls for the normal variation in weather across the year. Unusual weather can distort both the data and the seasonal factors. We control for both of these effects by integrating a weather adjustment step in the seasonal adjustment process. We use several indicators of weather, including temperature, snowfall and ...
Working Papers , Paper 15-5

Report
The money-output link: are F-tests reliable?

Research Paper , Paper 9328

Report
Sunspots, asset bubbles, and the store of value motive in overlapping generations models

Research Paper , Paper 9031

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