Exchange Rate Volatility and Monetary Policy Shocks

The study investigated the influence of innovations in monetary policy on the rate of exchange volatility in Nigeria. The research adopted vector error correction model as well as impulse response function and forecast error variance decomposition function in the estimation using two models derived in the study. Monthly data between the periods 2009 and 2019 were adopted for the research. Our findings show that in the long run; all the monetary policy variables have a significant long run correlation with volatility in the exchange rate; but that money supply and the rate of exchange seem to have significant short run impact on volatility in the exchange rate, the other variables such as liquidity ratio or monetary policy rate did not show a significant short run relationship with the volatility in the exchange rate. Further findings on the volatility impulse response and the forecast error variance decomposition suggest a significant link between volatility in the exchange rate and money supply though the link was much more pronounced. The use of monthly data shows that the managed exchange rate regime by the CBN seems to have the desired effect in exchange rate volatility and thus having a critical impact on inflationary spikes.

The time-varying and volatile macroeconomic effects of immigration

This paper studies the impact of immigration on the US macroeconomy. I identify structural vector autoregressions (SVARs) with time-varying parameters (TVPs) and stochastic volatility (SV) using a novel set of restrictions. The TVP-SV-SVARs are estimated on a quarterly sample including average labor productivity (ALP), hours worked, immigration, consumption, and term spread from 1953 to 2017. An immigration supply shock increases domestic ALP and hours worked over the business cycle horizons. Movements in immigration are explained by its own shock and to a lesser extent by the productivity and news shocks. IRFs driven by these shocks vary over the sample, especially around changes in immigration policy such as the Immigration Act of 1990. In contrast, the forecast error variance decompositions exhibit little change over the sample. Immigration plays an important role in the US macroeconomy.

Contribution of conventional bank lending for agricultural sector in Indonesia

This study examines the determinant contribution of conventional bank lending for the agricultural sector in Indonesia. The analysis method used in this research is the Vector Correction Model (VECM). The results showed that in the short term, there was no significant effect of the Non-Performing Loan (LogNPL), GDP of Agricultural Sector (LogPDB), and Agricultural Sector Credit Interest Rates (SBK). However, there is an effect of the LogNPL and LogPDB on the conventional bank lending for the agricultural sector in the long term. The LogNPL has a significant positive effect on the contribution of conventional bank lending to the agricultural sector. While the LogPDB has a significant negative effect on the contribution of conventional bank lending for the agricultural sector. The Impulse Response Function (IRF) analysis results show that shocks to the LogNPL respond negatively in the long run, shocks to the LogPDB respond positively in the long run, and shocks to the SBK respond negatively in the long run by conventional bank lending for the agricultural sector. Through the analysis of FEVD (Forecast Error Variance Decomposition), it is known that the biggest contribution to conventional bank lending for the agricultural sector is agricultural credit and GDP.

Smart advertising in prescription only medication; aligning it with prescriber’s or consumer’s behavior

Purpose This study has four objectives. First is to investigate and compare the immediate and carryover effects of four pharmaceutical marketing tools (prescriber detailing, medical events, journal ads and direct-to-consumer advertising [DTCA]) on sales. Based on the effect comparisons, the second objective is to determine whether advertising tools that are more compatible with prescriber’s behavior have superior impact on sales. Third is to examine empirical support for the argument that advertising directly to consumers, as a market follower versus leader, has a backfiring effect. Finally, this paper aims to assess the magnitude of variance in sales as a function of each advertising tool. Design/methodology/approach Data on unit sales and spending (on DTCA, journal ads, events and detailing) ranging 84 months are obtained for six prescription-only cholesterol-reducing brands. First, linearity is checked. Second, evolution versus stationarity is tested by applying the unit-root test. Third, potential endogeneity among variables is assessed with granger causality. Fourth, vector autoregressive model (VAR) that accounts for endogeneity and dynamic interactions is specified. Intercept, seasons and market share are added into the model specification as exogenous variables. Fifth, VAR with akaike selected lags and generalized impulse response are conducted. Finally, sales variance is decomposed with forecast error variance decomposition and Cholesky ordering. Findings A 10% increase on detailing or journal ads spending brought an immediate (one month) negative effect on sales in a market leader, whereas that same increase is insignificant in a market follower. A 10% increase on DTCA (vs detailing) spending led to a negative (vs positive) carryover effect for the market follower, giving empirical support to the backfiring effect of DTCA and partial evidentiary support suggested about prescriber friendly advertising. However, DTCA induces a larger short term and longer carryover effect in a market leader, with seven times more effect on sales than what detailing does. In addition, it explains 50% of the variation in sales. Originality/value The model applied captures extensive dynamics; hence, findings are robust. The analysis considered comparison in terms of prescriber friendly (vs not) advertising tools and brand market status and thus can make managers rethink strategy of advertising budget allocations. This study also introduced a new look onto DTCA and hence challenges the traditional thought held on consumer advertising response.

Predicting Water Availability in Water Bodies under the Influence of Precipitation and Water Management Actions Using VAR/VECM/LSTM

Recently, awareness about the significance of water management has risen as population growth and global warming increase, and economic activities and land use continue to stress our water resources. In addition, global water sustenance efforts are crippled by capital-intensive water treatments and water reclamation projects. In this paper, a study of water bodies to predict the amount of water in each water body using identifiable unique features and to assess the behavior of these features on others in the event of shock was undertaken. A comparative study, using a parametric model, was conducted among Vector Autoregression (VAR), the Vector Error Correction Model (VECM), and the Long Short-Term Memory (LSTM) model for determining the change in water level and water flow of water bodies. Besides, orthogonalized impulse responses (OIR) and forecast error variance decompositions (FEVD) explaining the evolution of water levels and flow rates, the study shows the significance of VAR/VECM models over LSTM. It was found that on some water bodies, the VAR model gave reliable results. In contrast, water bodies such as water springs gave mixed results of VAR/VECM.

Testing cointegration between workers' remittances and human capital formation in Sri Lanka

PurposeThis study investigates the long-run relationship between workers' remittances and human capital formation in Sri Lanka by using the macro-level time series data during the period of 1975–2020.Design/methodology/approachIn this study, the augmented Dickey–Fuller (ADF) and Philips–Perron (PP) unit root tests, the autoregressive distributed lag (ARDL) bounds cointegration technique, the Granger causality test, the forecast error variance decomposition technique and impulse response function analysis were employed as the analytical techniques.FindingsIn accordance with the results of unit root tests, the variables used in this study are mixed order. Results of cointegration confirm that workers' remittances in Sri Lanka have both long-run and short-run beneficial relationship with human capital formation. The Granger causality test results indicate that there is a two-way causal relationship between workers' remittances and human capital formation. The results of forecast error variance decomposition expose that innovation of workers' remittances contributes to the forecast error variance in human capital in bell shape. Further, the empirical evidence of impulse response function analysis reveals that a positive standard deviation shock to workers' remittances has an immediate significant positive impact on human capital formation in Sri Lanka for a period of up to ten years.Practical implicationsThis research provides insights into the workers' remittances in human capital formation in Sri Lanka. The findings of this study provides evidence that workers' remittances help to produce human capital formation.Originality/valueBy using the ARDL Bounds cointegration and other techniques in Sri Lanka, this study fills an important gap in academic literature.

On Spurious Causality, CO2, and Global Temperature

Stips et al. (2016) use information flows (Liang (2008, 2014)) to establish causality from various forcings to global temperature. We show that the formulas being used hinge on a simplifying assumption that is nearly always rejected by the data. We propose the well-known forecast error variance decomposition based on a Vector Autoregression as an adequate measure of information flow, and find that most results in Stips et al. (2016) cannot be corroborated. Then, we discuss which modeling choices (e.g., the choice of CO2 series and assumptions about simultaneous relationships) may help in extracting credible estimates of causal flows and the transient climate response simply by looking at the joint dynamics of two climatic time series.

Measuring monetary policy by money supply and interest rate: evidence from emerging economies

Although measuring monetary policy is a contentious issue in the literature, much less evidence on this issue is available for emerging economies. This paper aims to investigate the role of interest rate and money supply in measuring monetary policy in twelve emerging economies that target inflation through the analysis of Granger causality, impulse response function, and forecast error variance decomposition. The empirical results show that both money supply and interest rate are useful predictors for changes in inflation. Moreover, both show a comparable power to explain the variation of inflation. However, a rise in interest rate increases rather than decreases inflation, whereas money supply has a positive and expected effect on inflation. These findings suggest that interest rate may not fully capture the overall stance of monetary policy or interest rate has a limited effect on inflation.

Impact of credit risk and profitability on liquidity shocks of Namibian banks: an application of the structural VAR model

The main purpose of this paper was to investigate the relationship between banks’ credit risk and profitability and liquidity shocks in Namibia for the period 2009 to 2018 using the SVAR model. In estimating the SVAR regression model, granger causality, impulse-response functions and forecast error variance decomposition were employed and evaluated. The sample consisted of Namibian commercial banks. By auditing liquidity data between 2009 and 2018, empirical results showed that liquidity risk is caused by a combination of structural shocks. The granger causality, impulse-response functions and forecast error variance decomposition documented that credit risk (non-performing loans) is key factor affecting liquidity conditions in Namibia in the medium to long run. In addition, the empirical results showed that quality earnings (ROA) have minimal impact on liquidity conditions in the short run. Reforming assets quality policies and earnings quality policies can be valuable policy tools to minimize liquidity shortages and avoid insolvent banks in Namibia.