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Though an accumulating body of study has analysed monetary policy transmission in India, there are few studies examining the differential impact of monetary policy action. Against this backdrop, this study aims to analyse the differential impact of monetary policy on aggregate demand, aggregate supply and their components along with the general price level in India.

The study develops a structural macroeconometric model, which is primarily aggregate and eclectic in nature. The generalized method of movements is used for estimation of behavioural equations, while a Gauss–Seidel algorithm is used for model simulation purposes.

The paper presents the results of two policy simulations from the estimated model that highlight the differential impact of monetary policy. The first one, hike in the policy rate by 5% and second is a reduction in bank credit to the commercial sector by 10%. The results from the first policy simulation experiment reveal that interest hike has a significant negative impact on aggregate demand, aggregate supply and general price level. However, the maximum impact is borne by investment demand and imports followed by private consumption. While as among the components of aggregate supply maximum impact is born by infrastructure output followed by the manufacturing and services sector with the agriculture sector found to be insensitive in nature. The results from the second policy simulation experiment revealed that pure monetary shocks have a significant negative impact on aggregate demand, aggregate supply and general price level. However, the maximum impact is born by private consumption and imports followed by investment demand. While as among components of aggregate supply maximum impact is borne by infrastructure followed by the manufacturing and services sector with the agriculture sector found to be insensitive in nature. From both policy simulation experiments, the study highlighted the relative importance of the income absorption approach as opposed to the expenditure switching effect.

The results obtained in this study provides a strong framework for design the monetary policy framework. The results are in a view of the differential impact of monetary policy action among the components of both aggregate demand and aggregate supply. This reflection of differential impact has immense significance for the macroeconomic stabilization as the central bank will have to weigh the varying repercussion of its actions on different sectors. For instance, the decline in output after monetary tightening might be conceived as mild from an overall perspective, but it can be appreciable for some sectors. This differential influence will have an implication for policy design to care for distributional aspects, which otherwise could be neglected/disregarded. Similarly, the output decline may be as a result of either consumption postponement or a temporary slowdown in investment. However, the one emanating due to investment decline will have lasting growth implications compared to a decline in consumer demand. In addition, the relative strength of expenditure changing or expenditure switching policies of trade balance stabilization may have varying consequences in the aftermath of monetary policy shock. Accordingly information on the relative sensitiveness/insensitiveness of different sectors/ components of aggregate demand towards monetary policy actions furnish valuable insights to monetary authorities in framing appropriate policy.

The work carried out in the present paper is motivated by the fact that although a number of studies have examined the monetary transmission mechanism in India, a very few studies examining the differential impact of monetary policy action. However, to the best of the knowledge, there is no such studies, which have examined the differential impact of monetary policy in the structural macro-econometric framework. The paper will enrich the existing literature by providing a detailed account of the differential impact of monetary policy among the components of both aggregate demand and aggregate supply in response to an interest rate hike, as well as a decrease in the money supply.

This paper explores the evidence of a long-run co-movement between aggregate unemployment insurance spending and the labor force participation rate in the USA. The unemployment insurance (UI) program tends to expand during an economic downturn and contract during an expansion. UI may incentivize unemployment and may also facilitate better matching in the labor market. Statistical evidence of the presence of a co-movement will thus shed new light on their dynamics.

This research applies time-series econometric approach using monthly data from 1959:1 to 2020:3 to test threshold cointegration and estimate a threshold vector error-correction (TVEC) model. The estimates from the TVEC model investigating the nature of short-run dynamics.

The Enders and Siklos (2001) test find evidence of threshold cointegration between the two indicating the presence of long-run co-movement. The estimates from the TVEC model investigating the nature of short-run dynamics find evidence that the growth in aggregate UI spending and the growth in labor force participation rate adjust simultaneously to maintain the long-run co-movement above the threshold in the short run. The author also observes the same short-run dynamics for the growth in aggregate UI spending and the growth in the labor force participation rate for females.

This model is bi-variate by construction and does not address causality.

The author argues that the UI program positively impacts the female labor market outcomes, for example, better matching. This finding may explain the upward trend in the labor force participation rate for females in the USA.

The research findings may justify the transfer programs for minority and immigrants.

This is first research that analyzes the UI programs impact on the labor force participation using a macroeconometric approach. To the best of the author's knowledge, this is the first study in this genre.

Particles bed binding by selective cement activation (SCA) method is a computer-aided manufacturing (CAM) technique used to produce cementitious elements. A computer-aided design file is sliced to generate G-codes before printing. This paper aims to study the effect of key input parameters for slicer software on the final properties of printed products.

The one factor at a time (OFAT) methodology is used to investigate the impact of selected parameters on the final properties of printed specimens, and the causes for the variations in outcomes of each variable are discussed.

Finer aggregates can generate a more compact layer, resulting in a denser product with higher strength. Fluid pressure is directly determined by voxel rate (r_V); however, high pressures enable better fluid penetration control for fortified products; for extreme r_Vs, residual voids in the interfaces between successive layers and single-line primitives impair mechanical strength. It was understood that printhead movement along the orientation of the parts in the powder bed improved the mechanical properties.

The design of experiment (DOE) method assesses the influence of process parameters on various input printing variables at the same time. As the resources are limited, a fractional factorial plan is carried out on a subset of a full factorial design; hence, providing physical interpretation behind changes in each factor is difficult. OFAT aids in analyzing the effect of a change in one factor on output while all other parameters are kept constant. The results assist engineers in properly considering the influence of variable variations for future DOE designs.

The purpose of this paper is to measure TFP growth and job reallocation in the Vietnamese manufacturing industry after the Doimoi period.

The study uses firm-level panel data from Vietnam’s annual enterprise survey data for 2000–2016 period in the Vietnamese manufacturing industry using Olley–Pakes static and dynamic productivity decomposition methods.

The aggregate productivity estimated from the WRDG method increased 2.323 percent, of which over 40 percent is due to the reallocation toward more productive firms. Olley–Pakes dynamic decomposition according to ownership, scale and industry shows that the contribution of private and state-owned firms and the contribution of small and medium firms and large firms to the TFP growth are 133, −33 percent, 58.56 and 41.44 percent, respectively. The within-firm productivity and net entry components are the main reasons for TFP growth rather than reallocation. The results show that the composition of the aggregate TFPs, estimated from WRDG, OP, LP and ACF, is correlated very high (over 80 percent) except for net entry components.

The major limitation of this study is that the authors compute an aggregate productivity index using actual employment-based shares (still misallocation in labor), rather than optimal employment-based shares (no misallocation in labor).

Job reallocation between industries is attracting attention in developing countries, especially transition economies. However, knowledge about job reallocation among industries is limited. This paper assesses the level of job reallocation among private and state-owned firms, small and medium firms and large firms in Vietnam.

The authors explore the hypothesis that some movements in commodity prices are anticipated (news shocks) and can trigger aggregate fluctuations in small open emerging economies. This paper aims to discuss the aforementioned objective.

The authors build a multi-sector dynamic stochastic general equilibrium model with endogenous commodity production. There are five exogenous processes: a country-specific interest rate shock that responds to commodity price fluctuations, a productivity (TFP) shock for each sector and a commodity price shock. Both TFP and commodity price shocks are composed of unanticipated and anticipated components.

The authors show that news shocks to commodity prices lead to higher output, investment and consumption, and a countercyclical movement in the trade-balance-to-output ratio. The authors also show that commodity price news shocks explain about 24% of output aggregate fluctuations in the small open economy.

Given the importance of both anticipated and unanticipated commodity price shocks, policymakers should pay attention to developments in commodity markets when designing policies to attenuate the business cycles. Future research should investigate the design of optimal fiscal and monetary policies in SOE subject to news shocks in commodity prices.

This paper contributes to the knowledge of the sources of fluctuations in emerging economies highlighting the importance of a new source: news shocks in commodity prices.

The purpose of this study is to explore the link between aggregate production efficiency and the extent of linguistic clustering in Indonesia.

The author draws on the stochastic frontier model and applies it to the data on Indonesian provinces to compute the effects of various determinants on these provinces' aggregate production efficiency. The key determinant is the spatial index of linguistic clustering that the author believes has never been applied before in this context.

Linguistic clustering is an important determinant of aggregate production efficiency. Linguistic diversity is positively associated with productive efficiency if members of a specific linguistic group are not clustered beyond a certain level.

To the best of the author’s knowledge, this is the first study that links the spatial index of linguistic clustering (because of Massey and Danton) to production efficiency. In other words, the contribution of this study is to introduce a geographical dimension to the mainstream analysis of the association between ethnic diversity and economic performance.

The purpose of this paper is to evaluate and analyze impacts of the monetary policy (MP) – money aggregate and interest rate – on the exchange rate in Vietnam.

The study uses data over the period of 2008–2018 and applies the vector autoregression model, namely recursive restriction and sign restriction approaches.

The main empirical findings are as follows: a contraction of the money aggregate significantly leads to the real effective exchange rate (REER) depreciating and then appreciating; a tightening of the interest rate immediately causes the REER appreciating and then depreciating; and both the money aggregate and the interest rate strongly determine fluctuations of the REER.

The quantitative results imply that the MP affects the REER considerably.

Access to finance, especially by the poor and marginalized section of the population, is a prerequisite for creating employment opportunities, economic growth, poverty reduction and social cohesion. Access to finance makes transactions quicker, cheaper and safer. Most people around the world having an account in a formal financial institution serve as an entry point into formal financial sector. This study aims to analyze the status of financial inclusion in Assam with respect to demographic penetration, geographic penetration and usage ratio, i.e. credit–deposit ratio.

The study covers a period of 12 years from 2007–08 to 2018–19. Both the parametric and non-parametric statistical tools have been used to analyze the various dimensions of financial inclusion.

The study clearly indicates that there is a significant difference between Assam and aggregate India in financial inclusion and the status of Assam is somewhat lower as compared to the aggregate financial inclusion status of India. To achieve a satisfactory level of financial inclusion, it is not enough to open a bank account for the excluded people, but banks must look at flexibility and timeliness in services to offer a complete package to this segment of the population.

The study is a significant attempt to meet the shortcomings and improve banking coverage for achieving financial inclusion.

This study aims to investigate the dynamic interconnectedness of economic policy uncertainty (EPU), fiscal policy uncertainty (FPU) and monetary policy uncertainty (MPU) in four nations, the USA, Japan, Greece and South Korea, between 1998 and 2021.

To comprehend the cross-category/cross-country evolution of uncertainty connectedness, the authors use the conditional connectedness approach. By using an inclusive network, this strategy lessens the bias caused by omitted variables. The TVP-VAR method is advantageous as it eliminates outliers that may potentially skew the results and reduces the bias caused by picking arbitrary rolling windows.

Based on the findings, aggregate EPU is a net transmitter of policy uncertainties across all countries when conditional-country connectedness is used. MPU receives significantly more spillovers than FPU does across all countries, even though both are primarily recipients of uncertainties. The USA appears to be a transmitter of categorical spillovers before COVID-19, while Greece appears to be a net receiver of all category spillovers in terms of category-specific connectedness. The existence of extreme global events is also seen to cause an increase in category-specific and country-specific connectedness. Additionally, the authors report that conditional country-specific connectedness is greater than conditional category-specific connectedness.

This study expands existing literature in several ways. Firstly, the authors use a novel conditional connectedness approach, which has not been used to untangle cross-category/cross-country policy uncertainty connectedness. Secondly, they use the TVP-VAR approach which does not depend on rolling windows to understand dynamic connectedness. Thirdly, they use an expanded number of countries in their analysis, a departure from existing studies that have in most cases used two countries to understand categorical EPU connectedness.

It has been demonstrated in the US market that expected market excess returns can be predicted using the average higher-order moments of all firms. This study aims to empirically test this theory in emerging markets.

Two measures of average higher moments have been used (equal-weighted and value-weighted) along with the market moments to predict subsequent aggregate excess returns using the linear as well as the quantile regression model.

The authors report that both equal-weighted skewness and kurtosis significantly predict subsequent market returns in two countries, while value-weighted average skewness and kurtosis are significant in predicting returns in four out of nine sample markets. The results for quantile regression show that the relationship between the risk variable and aggregate returns varies along the spectrum of conditional quantiles.

This is the first study that investigates the impact of third and fourth higher-order average realized moments on the predictability of subsequent aggregate excess returns in the MSCI Asian emerging stock markets. This study is also the first to analyze the sensitivity of future market returns over various quantiles.