Карамышева Мадина Ринатовна

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

This version June 2021

ABSTRACT

We study the effects of fiscal consolidations in the United States and their propagation in the production network. We use a narrative approach to identify fiscal adjustments which are exogenous to output fluctuations. Then we apply spatial econometric techniques to separate the total effect of fiscal adjustments into a direct and network component. We find that fiscal adjustments based on increased taxation are more recessionary than those based on spending cuts. Moreover, one-quarter of the difference in their total output effect is explained by the stronger network propagation of taxes relative to government spending.

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3971565

2. German N., M. Karamysheva, "Fiscal Multiplier and the Size of Government Spending Shock. The case of the U.S." (Working Paper)

This version February 2022

ABSTRACT

This paper investigates whether the fiscal multiplier depends negatively on the size of the government spending shock. We build our hypothesis on behavioral arguments and check it empirically using U.S. data. In doing so, we adopt a non-linear Local Projection method. We address possible endogeneity issues by using government military spending and illustrate that our results are non-sensible to these concerns. Finally, we limit our analysis to the government consumption multiplier, as our hypothesis suggests strong non-constancy in this respect. We find a strong negative relationship between the government spending multiplier and the size of the shock. Results are robust to different subsamples, fiscal foresight, business cycle, and different identification schemes.

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4027245

3. Favero C., M. Karamysheva, "Design of Fiscal Adjustments: Plans versus Shocks" (Working Paper)

This version January 2021

ABSTRACT

This paper analyzes the measurement of the output effects of fiscal stabilization policies, by assessing the relevance of different methods in determining the heterogeneity of available results and by evaluating comparatively the different approaches proposed in the literature. We compare fiscal plans and fiscal shocks in the U.S. over the period 1978q1-2014q4 by estimating the truncated moving average (MA). We show that plans nest shocks. Our results suggest that the use of shocks instead of plans causes the size and the interpretation of fiscal multipliers to be affected.

4. Craig B., Karamysheva M., Salakhova D., "Do market-based networks reflect true exposures between banks?" (Working Paper)

This version January 2022

ABSTRACT

Due to the lack of or poor access to the data on real exposures between banks, several methods have been proposed to reconstruct a network using market data. However, what does this market-based network represent? In this paper, we replicate several well-known methods to construct market-based networks. Next, we build networks based on true exposures through loans and securities holdings. Then we provide graphical analysis as well as a comparison of network characteristics across different types of networks and different time periods. Our regression analysis sheds light on which balance-sheet exposures better explain the links perceived by the market. Our findings suggest that while global network structure remains stable, networks evolve over time. Regression analysis shows that (i) market identifies two banks as connected when they have similar business models defined by overlapping portfolios of loans (IL); (ii) market identifies two banks as connected when they lend to each other using interbank lending (DL), only when market network is cleaned up the noise and co-movement; (iii) market on average does not capture common exposures to similar securities and direct securities on top of co-movement and controls.

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4626466 

5. Gafarov B., Karamysheva M., Polbin A., Skrobotov A., "Wild inference for wild SVARs with application to heteroscedasticity-based IV" (Working Paper)

This version November 2024

ABSTRACT

Structural vector autoregressions are used to compute impulse response functions (IRF) for persistent data. Existing multiple-parameter inference requires cumbersome pretesting for unit roots, cointegration, and trends with subsequent stationarization. To avoid pretesting, we propose a novel dependent wild bootstrap procedure for simultaneous inference on IRF using local projections (LP) estimated in levels in possibly nonstationary and heteroscedastic SVARs. The bootstrap also allows efficient smoothing of LP estimates. 

We study IRF to US monetary policy identified using FOMC meetings count as an instrument for heteroscedasticity of monetary shocks. We validate our method using DSGE model simulations and alternative SVAR methods. 

https://arxiv.org/abs/2407.03265 

1) Опыт работы в оргкомитете студенческого конкурса «Олимпиада: Я профессионал» в сфере финансов (2017 и 2018). (Благодарственное письмо проректора НИУ ВШЭ. Июль 2018 г.)

2) Член экспертной комиссии в области экономики и финансов Открытого конкурса научных работ студентов НИУ ВШЭ (НИРС).

3) Член Ученого совета магистратуры Стратегические корпоративные финансы.

4) Проведение собеседований с иностранными студентами (магистратура Стратегические корпоративные финансы)

5) Член оргкомитета Международного научного семинара ФЭН / МИЭФ.

6) Член оргкомитета серии совместных онлайн-семинаров по макро-финансам (Банк России, НИУ ВШЭ ФЭС / МИЭФ, РЭШ).

7) Опыт рецензента в Российский и международных журналах