Advances in Empirical Methods for Time Series and Forecasting in Unstable Environments

Introduction

The environment we live in is both complex and time-varying. Examples of recent instabilities include the recent financial crises, the COVID-19 pandemic, and the war in Ukraine, which have substantially altered our world. Currently, however, the way researchers implement forecasts and estimate the effects of economic policies is based on methods that either impose restrictive assumptions on the nature of instabilities or quickly become computationally demanding in the presence of instabilities.

Project Proposal

This project proposes to develop a local projection-based estimator for time-varying parameter models and their impulse response functions in unstable environments, which we refer to as the “time-varying parameter local projection” estimator (or “TVP-LP” in short).

Objectives

The proposed estimator is expected to provide a feasible approach to:

1. Conveniently and flexibly estimate economic models in unstable environments.
2. Forecast and assess the effects of economic policies.

Generalization and Applicability

The proposed estimator can be generalized to include instrumental variables and can be applied in vector autoregressive models with external instruments while being robust to the presence of instabilities. The proposed methodology is expected to have widespread applicability given the increasing interest in using convenient local projection estimators and the substantial evidence of instabilities in macroeconomic models.

Comparison with Conventional Models

In contrast to conventional time-varying parameter VAR models, the proposed time-varying parameter local projection estimator is robust to the presence of non-invertibility due to omitted variables and misspecification. Additionally, its estimation is less computationally challenging.

Advantages

The advantages of the methodology will be illustrated in terms of:

• Forecasting ability
• Evaluation of the effects of economic policy (in particular, fiscal policy)