The primary aim of the paper is to place current methodological discussions on empirical modeling contrasting the 'theory first' versus the 'data first' perspectives in the context of a broader methodological framework with a view to constructively appraise them. In particular, the paper focuses...

In this paper, we test cointegration between GDP and Public consumption of the Republic of North Macedonia, for quarterly data of twenty years' time series (2000Q1-2019Q4). We present results of two methods for cointegration test: first, residual regression test table and second, Engle & Granger...

This paper exploits the homogeneity feature of the Singapore private residential condominium market and constructs matched home purchase price and rental price series using the repeated sales method. These matched series allow us to conduct time series analysis to examine the long-term present...

Purpose: Given the severity and the length of the crisis caused by the COVID-19 pandemic, information on the financial impact of the pandemic becomes useful to enterprises who wish to arm themselves with strategies and policies, designed to combat the effects of similar crises. Such information...

The sustainability of the Nigerian fiscal deficit along with the role of the dynamics of government revenues and spending in adjusting the size of the deficit is examined using annual data from 1961 to 2014. After allowing for structural breaks, the study finds evidence of a cointegration...

Although a large number of recent studies employ the buy-and-hold abnormal return (BHAR) methodology and the calendar time portfolio approach to investigate the long-run anomalies, each of the methods is a subject to criticisms. In this paper, we show that a recently introduced calendar time...

I translate familiar concepts of discrete-time time-series to continuous-time equivalent. I cover lag operators, ARMA models, the relation between levels and differences, integration and cointegration, and the Hansen-Sargent prediction formulas

We introduce the multivariate Ornstein-Uhlenbeck and discuss how it generalizes a vast class of continuous-time and discrete-time multivariate processes. Relying on the simple geometrical interpretation of the dynamics of the Ornstein-Uhlenbeck process we introduce cointegration and its...

Bayesian inference requires an analyst to set priors. Setting the right prior is crucial for precise forecasts. This paper analyzes how optimal prior changes when an economy is hit by a recession. For this task, an autoregressive distributed lag model is chosen. The results show that a sharp...