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SPIN-RSCI: 6208-4344
ORCID: 0000-0003-3597-3489
ResearcherID: O-4996-2016
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Madina Karamysheva

  • Madina Karamysheva has been at HSE since 2016.

Education and Degrees

  • 2016

    PhD
    Bocconi University

  • 2009

    Master's in Applied Mathematics and Information Science
    Voronezh State University

  • 2007

    Bachelor's in Applied Mathematics and Information Science
    Voronezh State University

Awards and Accomplishments

Student Term / Thesis Papers

Full list of of student term / thesis papers

Courses (2018/2019)

Courses (2017/2018)

Courses (2016/2017)

Publications1

Chapter Favero C., Karamysheva M. What Do We Know about Fiscal Multipliers?, in: Rethinking Fiscal Policy after the Crisis. Cambridge University Press, 2017. doi P. 443-482. doi

Working Papers

1. Karamysheva M.,"Can Uncertainty Explain the Heterogeneous Output Effects of Fiscal Adjustments?" (Working Paper)

This version July 2018

ABSTRACT

Recent empirical evidence suggests that fiscal consolidations mainly based on tax hikes have a more recessionary impact on economic growth relative to those based on expenditure cuts. This paper evaluates the output effects of fiscal adjustment plans identified through the narrative approach. I incorporate fiscal plans into a vector autoregression model to investigate the channels of transmission of fiscal consolidations. In addition to a direct effect I explore two indirect effects, in particular, whether monetary policy or uncertainty could explain the heterogeneous output effects of fiscal adjustment plans. It appears, that uncertainty channel is more important among the two.

2. Briganti E., Favero C., M. Karamysheva, "The Network Effects of Fiscal Adjustments" (Working Paper)

This version July 2018 

ABSTRACT

A large and increasing body of empirical evidence has established that fiscal adjustments based on government spending cuts are less costly in terms of losses in output growth than those based on tax increases. We show that the propagation of fiscal adjustment plans through the industrial network can in theory explain this evidence and that it does so in practice for the US economy. The heterogenous effects of tax-based and expenditure-based adjustments might depend on the difference in their propagation channels in the network of industries. A tax-based adjustment plan is mainly a supply shock which propagates downstream (from supplier industries to customer industries) while an expenditure based plan is a demand shock which propagates upstream (from customer industries to supplier industries). Empirical investigation of these channels on US data based on Spatial Vector Autoregressions reveals that tax based plans propagate through the network with an output multiplier of -2.05, statistically different from zero, while the propagation of expenditure based plans generates an output multiplier of -0.77, not statistically different from zero.

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3206782

 WebAppendix (PDF, 2,26 Мб)

3. Favero C., M. Karamysheva, "The Measurement of the Output Effect of Fiscal Adjustments" (Working Paper)

4. Karamysheva M., E. Seregina, "Prudential policies: transmission channels and impact on systemic risk" (Working Paper)

This version July 2018 

ABSTRACT

We investigate the impact of regulatory interventions on systemic risk measured by SRISK and CoVaR indicators. We look into the impact of prudential tools on systemic risk at the country level. We check for the average policy impact as well as the differential between the groups of countries. We apply the spatial econometric approach to decompose the policy impact into direct and indirect impact. Our estimations confirm the importance of macroprudential policies for systemic risk reduction. Importantly for SRISK capturing the vulnerability to the overall system shocks most of the reduction comes from the indirect e↵ect of the network (85% of total impact). Instead once we measure the contribution to systemic risk via CoVaR the impact is split more evenly (50% to 50%). We obtain similar results when splitting the country-level indicators into banking and non-banking sectors. As expected, policy impact is typically more relevant (and sizeable) for the banking sector. The network effect however stays important for both sectors.

 

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