POPULATION GROWTH INDUCED AND HOUSEHOLDS FINANCIAL VULNERABILITY IN NIGERIA

Nigeria has been recording a rapid increase in its population over the years. This reality has posed a serious concern for the welfare of households especially as the increase in population growth puts households at the risk of financial vulnerability. Based on this, this study is on the move to examined the impact population growth induced has on household in Nigeria. The study made use of secondary data obtained from World Bank and the Central Bank statistical bulletine spanning from 1981 to 2020 to analyze the impact of population growth induced and its financial vulnerability on household using a structural vector autoregressive model (SVAR). After the analysis, the study found out that in the long run, an increase in financial vulnerability, due to an increase in population growth decreases household welfare in Nigeria. Hence, this study recommends that the Nigerian legislature should formulate a law against rapid population growth induced to ensure that the increase in population does not outscore the means of subsistence. JEL: H10; H31 <p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0789/a.php" alt="Hit counter" /></p>

Dynamic Characteristics of Oil Attributes and Their Market Effects

The commercial and financial attributes of oil have significantly changed the evolution characteristics of prices and returns of the international crude oil market. Using monthly data from April 2003 to October 2020, this paper identifies dynamic characteristics of oil’s commercial and financial attributes based on the structural vector autoregressive model (SVAR) and further analyzes their market effects with different attributes. The result shows that there are situations of commercial and financial attributes dominating, and dual attributes co-dominating for oil. Furthermore, their durations account for 51%, 23%, and 26% respectively, of the full sample. Besides, the reactions of crude oil price or return to the different properties of oil are heterogeneous. Specifically, the dual attributes of oil play the most important role in the price evolution of the international crude oil market, which is 80.851. There are significant differences among the impact of different attributes of oil on the evolution of international crude oil market returns, which are 0.009, −0.008, and −0.004, respectively. Then, some relevant recommendations for policy-makers and investors based on the above research conclusions are also put forward.

A Spatial Panel Structural Vector Autoregressive Model with Interactive Effects and Its Simulation

The existing spatial panel structural vector auto-regressive model can effectively capture the time and spatial dynamic dependence of endogenous variables. However, the hypothesis that the common factors have the same effect for all spatial units is unreasonable. Therefore, incorporating time effects, spatial effects, and time-individual effects, this paper develops a more general spatial panel structural vector autoregressive model with interactive effects (ISpSVAR) that can reflect the different effects of common factors on different spatial units. Additionally, based on whether or not the common factors can be observed, this paper proposes procedures to estimate ISpSVAR separately and studies the finite sample properties of estimators by Monte Carlo simulation. The simulation results show the effectiveness of the proposed ISpSVAR model and its estimation procedures.

INSTRUMENTAL VARIABLE ESTIMATION OF STRUCTURAL VAR MODELS ROBUST TO POSSIBLE NONSTATIONARITY

This paper considers the estimation of dynamic causal effects using a proxy structural vector-autoregressive model with possibly nonstationary regressors. We provide general conditions under which the asymptotic normal approximation remains valid. In this case, the asymptotic variance depends on the persistence property of each series. We further provide a consistent asymptotic covariance matrix estimator that requires neither knowledge of the presistence properties of the variables nor pretests for nonstationarity. The proposed consistent covariance matrix estimator is robust and is easy to implement in practice. When all regressors are indeed stationary, the method becomes the same as the standard procedure.

Structural estimates of the South African sacrifice ratio

This paper estimates the output cost of fighting inflation—the sacrifice ratio—for the South African economy using quarterly data spanning the period 1998Q1–2019Q3. To compute the sacrifice ratio, the structural vector autoregressive model developed by Cecchetti and Rich (2001) based on Cecchetti (1994) is employed. Our findings show us a small sacrifice ratio, which lies within the range 0.00002–0.231 per cent with an average of 0.031 per cent, indicating a low level of output to be sacrificed while fighting inflation. Hence, the reserve bank is recommended to sustain an inflation rate within the target range and reap the benefits of a predictable and stable price path, as restrictive monetary policy has only a transitory effect on real variables like output.

Identification at the Zero Lower Bound

I show that the zero lower bound (ZLB) on interest rates can be used to identify the causal effects of monetary policy. Identification depends on the extent to which the ZLB limits the efficacy of monetary policy. I propose a simple way to test the efficacy of unconventional policies, modeled via a “shadow rate.” I apply this method to U.S. monetary policy using a three‐equation structural vector autoregressive model of inflation, unemployment, and the Federal Funds rate. I reject the null hypothesis that unconventional monetary policy has no effect at the ZLB, but find some evidence that it is not as effective as conventional monetary policy.

Credit supply shocks and the Great Depression in Germany

At the peak of the Great Depression in mid-1931, Germany experienced a severe banking crisis. We study to what extent credit constraints contributed to the downturn by fitting a structural vector autoregressive model with data from January 1925 to September 1935. Adverse credit supply shocks contributed strongly to the downturn especially at the time of the 1931 banking crisis. Before that, credit supply shocks had also contributed to the expansion phase preceding the depression. We also find that aggregate demand and U.S. business cycle shocks were the primary drivers of the German Great Depression.

Information Search and Financial Markets under COVID-19

The discovery and sudden spread of the novel coronavirus (COVID-19) exposed individuals to a great uncertainty about the potential health and economic ramifications of the virus, which triggered a surge in demand for information about COVID-19. To understand financial market implications of individuals’ behavior upon such uncertainty, we explore the relationship between Google search queries related to COVID-19—information search that reflects one’s level of concern or risk perception—and the performance of major financial indices. The empirical analysis based on the Bayesian inference of a structural vector autoregressive model shows that one unit increase in the popularity of COVID-19-related global search queries, after controlling for COVID-19 cases, results in 0.038 – 0.069 % of a cumulative decline in global financial indices after one day and 0.054 – 0.150 % of a cumulative decline after one week.

When Banks Punch Back

In the presence of adverse macroeconomic shocks, simultaneous capital losses in multiple banks can prompt them to contract their balance sheets. These bank responses generate externalities that propagate in the form of macro-financial feedback loops. This paper develops a credit response and externalities analysis model (CREAM) that integrates a disaggregated banking sector into an otherwise standard macroeconomic structural vector autoregressive model. It shows that accounting for macro-financial feedback loops can significantly affect macroeconomic outcomes and bank-specific stress tests results. The heterogeneity in bank lending responses matters: it determines how each bank fares under adverse conditions and the external effects that banks impose on each other and on economic activity. The model can thus be used to assess the contributions of individual banks to systemic risk along the time dimension.