External Shocks and Their Transmission Channels in Nigeria: A Dynamic Stochastic General Equilibrium Approach

The study examines the sources of external shocks and investigates their transmission channels in Nigeria using the trade-weighted variables from the country’s five top trading partners. Based on the assumption of the small open economy model, the study adopts the New Keynesian Dynamic Stochastic General Equilibrium Model on quarterly data between 1981 and 2018 using the Bayesian estimation technique. Findings from the study reveal that external shocks have a temporary and short-lived effect on the Nigerian economy. In addition, the article shows that oil price, foreign output, and foreign inflation shock have positive impacts on output gap and inflation, while the impact of foreign interest rate shock on the output gap and inflation is negative and not significant. The study also reveals that external shocks collectively explain 86% and 39%of total fluctuations in the output gap and inflation, respectively. Lastly, the study finds that external shocks transmit to the Nigerian economy via different channels. The study, therefore, concludes that terms of trade and exchange rate channels are the dominant transmitters of external shocks in Nigeria. Based on the findings from the study, important policy implications are highlighted.

Model Uncertainty and Financial Frictions: Implications for Optimal Monetary Policy

The last decades proved that policymaking without considering uncertainty is impracticable. In an environment of uncertainty, policymakers have doubts about the policy models they routinely use. This paper focuses specifically on the situation where uncertainty on the financial side of the economy leads to misspecification in the policy model. We describe a coherent strategy for policymakers who are averse to model misspecification and analyze optimal policy design in the face of Knightian uncertainty. To do so, we augment a financial dynamic stochastic general equilibrium model with model misspecification in a simple minimax framework where the central bank plays a zero-sum game versus a hypothetical evil agent. The policy is tailored to insure against the worst-case outcomes. We show that model ambiguity on the financial side requires a passive monetary policy stance. However, if the uncertainty originates from the supply side of the economy, an aggressive response of interest rate is required. We also show the impact of an additional macroprudential tool on the dynamics of the economy.

Recent models for long range forecasting of Southwest monsoon rainfall in India

India has a long tradition of scientific work or, long range forecasting of the southwest monsoon ever since the times of Blanford and Walker In the early Parts of this century, the recent decades have witnessed increased research in regard to the development of new long range forecast models in the India Meteorological Department which have, given correct long range (seasonal) forecasts of southwest monsoon rainfall, over the country as a whole, during, the successive four year~, 1988 to 1991, Presently, four models namely, Para-metric Power Regression, Dynamic Stochastic Transfer and Improved Multiple Regression models are being used for formulating the seasonal forecast of monsoon rainfall over the country as a whole, The forecast is issued in two stages, In the first stage a tentative inference which is qualitative in nature is issued before the middle of April based mainly on the Parametric model which utilizes signals from 16 regional and global parameters that are related to land, ocean and atmospheric forcing and show physical linkages with monsoon. In the second stage, a firm quantitative forecast is issued towards the end of the May and is based on the remaining three models mentioned above, although higher weight age is given to the Power Regression Model which has shown encouraging performance during the last four years. In this paper, these recently developed models and the scientific basis underlying these are discussed, Data on validation of these Operational models, used for the long range forecast during the past four years (1988-91) are also presented.

VALIDATING DSGE MODELS WITH SVARS AND HIGH-DIMENSIONAL DYNAMIC FACTOR MODELS

A popular validation procedure for Dynamic Stochastic General Equilibrium (DSGE) models consists in comparing the structural shocks and impulse-response functions obtained by estimation-calibration of the DSGE with those obtained in an Structural Vector Autoregressions (SVAR) identified by means of some of the DSGE restrictions. I show that this practice can be seriously misleading when the variables used in the SVAR contain measurement errors. If this is the case, for generic values of the parameters of the DSGE, the shocks estimated in the SVAR are not “made of” the corresponding structural shocks plus measurement error. Rather, each of the SVAR shocks is contaminated by noncorresponding structural shocks. We argue that High-Dimensional Dynamic Factor Models are free from this drawback and are the natural model to use in validation procedures for DSGEs.

Systematically Understanding Cybersecurity Economics: A Survey

Insights in the field of cybersecurity economics empower decision makers to make informed decisions that improve their evaluation and management of situations that may lead to catastrophic consequences and threaten the sustainability of digital ecosystems. By drawing on these insights, cybersecurity practitioners have been able to respond to many complex problems that have emerged within the context of cybersecurity over the last two decades. The academic field of cybersecurity economics is highly interdisciplinary since it combines core findings and tools from disciplines such as sociology, psychology, law, political science, and computer science. This study aims to develop an extensive and consistent survey based on a literature review and publicly available reports. This review contributes by aggregating the available knowledge from 28 studies, out of a collection of 628 scholarly articles, to answer five specific research questions. The focus is how identified topics have been conceptualized and studied variously. This review shows that most of the cybersecurity economics models are transitioning from unrealistic, unverifiable, or highly simplified fundamental premises toward dynamic, stochastic, and generalizable models.

How influential are COVID–19 data points? A fresh look at an estimated small scale DSGE model for the Philippines

Shocks emanating from the global pandemic continue to reshape the macroeconomic landscape—dimming national growth prospects, prolonging widespread financial distress among households, firms, and governments and heightening uncertainty. Using a small-scale New Keynesian Dynamic Stochastic General Equilibrium (DSGE) model for the Philippines, we examine the model’s sensitivity to COVID-19 datapoints or extreme observations. Relative to estimates during the base period (2002Q1 to 2019Q4), the inclusion of extreme datapoints worsens the model’s log data density progressively, from the consideration of the first quarter of 2020 to the full sample – an indication that shock propagation mechanisms associated with COVID–19 and other natural disasters should be integrated into the model. Even with the inclusion of said extreme observations, however, the model’s parameters are identified, provided identification schemes are evaluated at posterior median estimates. Judging from the sets of parameter estimates relative to the base sample, the effects of extreme observations are found to be non–uniform, especially the size of the shocks. But there are other parameters, notably those that are embedded in the Taylor rule, which are relatively as stable as some household related parameters. These results imply that the size of standard errors for demand, supply, and monetary policy shocks adjust to partially capture the impact of extreme datapoints.

The Role of Wage Formation in Empirical Macroeconometric Models

The specification of model equations for nominal wage setting has important implications for the properties of macroeconometric models and requires system thinking and multiple equation modeling. The main models classes are the Phillips curve model (PCM), the wage–price equilibrium correction model (WP-ECM), and the New Keynesian Phillips curve (NKPCM). The PCM was included in the macroeconometric models of the 1960s. The WP‑ECM arrived in the late 1980s. The NKPCM is central in dynamic stochastic general equilibrium models (DSGEs). The three model classes can be interpreted as different specifications of the system of stochastic difference equations that define the supply side of a medium-term macroeconometric model. This calls for an appraisal of the different wage models, in particular in relation to the concept of the non-accelerating inflation rate of unemployment (NAIRU, or natural rate of unemployment), and of the methods and research strategies used. The construction of macroeconomic model used to be based on the combination of theoretical and practical skills in economic modeling. Wage formation was viewed as being forged between the forces of markets and national institutions. In the age of DSGE models, macroeconomics has become more of a theoretical discipline. Nevertheless, producers of DSGE models make use of hybrid forms if an initial theoretical specification fails to meet a benchmark for acceptable data fit. A common ground therefore exists between the NKPC, WP‑ECM, and PCM, and it is feasible to compare the model types empirically.