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Studies linking monetary policy to inflation and unemployment rates in the context of the Phillips curve are limited to conventional economics. On the other hand, research related to application of the dual monetary policy is limited to discussion of monetary policy transmission lines, especially in Islamic banking channels. Therefore, this study aims to determine the monetary policy response in implementation of the dual monetary policy to two important indicators in the macro economy, namely, inflation and unemployment. In addition, the study reveals the relevance of the Phillips curve in Indonesia.

The method used is vector auto regression vector autoregression (VAR) with monthly data from February 2005 to October 2016 for the first model and semi-annual data from February 2005 to August 2017 for the second model. Analysis of VAR estimation in this research uses the impulse response function (IRF) to analyze the degree of sensitivity or responsiveness to a shock between variables and the variance decomposition (VD) application to analyze how the proportion of each independent variable’s contribution affects the money supply.

The result shows that monetary policy has responded appropriately to the problems of inflation and unemployment. However, inflation generates a bigger response than unemployment. Bank Indonesia considers the inflation expectations aspect of both conventional and Islamic references. Finally, the concept of the Phillips curve proves to be irrelevant in Indonesia.

The central bank is expected to build a more effective policy for transmission from the monetary sector to the real sector to effectively overcome the problems of inflation and unemployment. Furthermore, Indonesia needs to increase policies to overcome problems on the supply side.

The results of this study provide new insights into application of the dual monetary policy toward inflation and unemployment.

The purpose of this paper is to empirically analyze the impact of social inclusion factors and foreign fund inflows on reducing gender-based unemployment in India.

A time series data set for the period of 1991–2021 has been considered, and an autoregressive distributed lag methodology has been applied to measure the short- and long-run impact of social inclusion and foreign fund inflows on reducing gender-based unemployment in India.

According to the study’s findings, both social inclusion and foreign fund inflows are critical factors for reducing male unemployment. However, in the case of female unemployment, only social inclusion factors play an important role, whereas foreign fund inflows have no role in it.

Analyzing the factors that affect gender-based unemployment has always been a grey area in literature. There are very few studies that capture gender-based unemployment in India, making this study a novice contribution. Second, it examines the relationship between foreign fund inflows, social inclusion and unemployment, which is another novel area of investigation. Finally, this study provides comprehensive and distinct results for both male and female unemployment that can help policymakers devise gender-based unemployment policies.