Madina Karamysheva
- Research Fellow: Faculty of Economic Sciences / Laboratory for Banking Studies
- Associate Professor: Faculty of Economic Sciences / School of Finance
- Madina Karamysheva has been at HSE University since 2016.
Education and Degrees
Bocconi University
Voronezh State University
Voronezh State University
Awards and Accomplishments
Best Teacher — 2018–2019
Courses (2024/2025)
- International Finance (Master’s programme; Faculty of Economic Sciences field of study Finance and Credit, field of study Economics, field of study Finance and Credit, field of study Finance and Credit, field of study Finance and Credit, field of study Finance and Credit, field of study Economics; 2 year, 1, 2 module)Eng
- International Finance (Mago-Lego; 1, 2 module)Eng
- International Finance (Master’s programme; Faculty of Economic Sciences; 1 year, 1, 2 module)Eng
- Methodological Research Seminar (Bachelor’s programme; Faculty of Economic Sciences; 4 year, 1 module)Rus
- Methodological Research Seminar (Master’s programme; Faculty of Economic Sciences; 1 year, 3, 4 module)Eng
- Times Series Econometrics (Bachelor’s programme; Faculty of Economic Sciences field of study Economics, field of study Economics; 4 year, 1, 2 module)Eng
- Past Courses
Courses (2023/2024)
- International Finance (Master’s programme; Faculty of Economic Sciences field of study Finance and Credit, field of study Finance and Credit, field of study Finance and Credit, field of study Finance and Credit, field of study Finance and Credit, field of study Economics, field of study Economics, field of study Economics; 2 year, 1, 2 module)Eng
- International Finance (Mago-Lego; 1, 2 module)Eng
- International Finance (Master’s programme; Faculty of Economic Sciences; 1 year, 1, 2 module)Eng
- International Finance (Postgraduate course; 2 year, 1 semester)Eng
- Methodological Research Seminar (Bachelor’s programme; Faculty of Economic Sciences; 4 year, 1 module)Rus
- Methodological Research Seminar (Master’s programme; Faculty of Economic Sciences field of study Finance and Credit, field of study Finance and Credit, field of study Finance and Credit; 1 year, 3, 4 module)Eng
- Times Series Econometrics (Bachelor’s programme; Faculty of Economic Sciences field of study Economics, field of study Economics; 4 year, 1, 2 module)Eng
Courses (2022/2023)
- International Finance (Master’s programme; Faculty of Economic Sciences field of study Finance and Credit, field of study Finance and Credit, field of study Finance and Credit; 1 year, 1, 2 module)Eng
- International Finance (Mago-Lego; 1, 2 module)Eng
- International Finance (Master’s programme; Faculty of Economic Sciences field of study Economics, field of study Economics, field of study Finance and Credit, field of study Finance and Credit; 2 year, 1, 2 module)Eng
- International Finance (Master’s programme; St.Petersburg School of Economics and Management; 2 year, 1, 2 module)Eng
- Methodological Research Seminar (Master’s programme; Faculty of Economic Sciences field of study Finance and Credit, field of study Finance and Credit; 1 year, 1, 2 module)Eng
- Times Series Econometrics (Bachelor’s programme; Faculty of Economic Sciences field of study Economics, field of study Economics; 4 year, 1, 2 module)Eng
Courses (2021/2022)
- International Finance (Postgraduate course; 2 year, 1 semester)Eng
- International Finance (Master’s programme; Faculty of Economic Sciences field of study Finance and Credit, field of study Finance and Credit, field of study Economics; 2 year, 1, 2 module)Eng
- International Finance (Master’s programme; St.Petersburg School of Economics and Management; 2 year, 1, 2 module)Eng
- International Finance (Master’s programme; Faculty of Economic Sciences; 1 year, 1, 2 module)Eng
- Methodological Research Seminar (Master’s programme; Faculty of Economic Sciences; 1 year, 1, 2 module)Eng
- Times Series Econometrics (Bachelor’s programme; Faculty of Economic Sciences field of study Economics, field of study Economics; 4 year, 1, 2 module)Eng
Courses (2020/2021)
- International Finance (Postgraduate course; 2 year, 1 semester)Eng
- International Finance (Master’s programme; Faculty of Economic Sciences field of study Economics, field of study Finance and Credit, field of study Finance and Credit; 2 year, 1, 2 module)Eng
- International Finance (Master’s programme; Faculty of Economic Sciences; 1 year, 1, 2 module)Eng
- Methodological Research Seminar (Master’s programme; Faculty of Economic Sciences; 1 year, 1, 2 module)Eng
- Research Project Seminar (Optional course (faculty); Faculty of Economic Sciences; 1-3 module)Rus
- Times Series Econometrics (Bachelor’s programme; Faculty of Economic Sciences field of study Economics, field of study Economics; 4 year, 1, 2 module)Eng
Working Papers
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., "Policymaker meetings as heteroscedasticity shifters: Identification and simultaneous inference in unstable SVARs" (Working Paper)
This version July 2024
ABSTRACT
We propose a novel approach to identification in structural vector autoregressions (SVARs) that uses external instruments for heteroscedasticiy of a structural shock of interest.
This approach does not require lead/lag exogeneity for identification, does not require heteroskedasticity to be persistent, and facilitates interpretation of the structural shocks.
To implement this identification approach in applications, we develop a new method for simultaneous inference of structural impulse responses and other parameters, employing a dependent wild-bootstrap of local projection estimators. This method is robust to an arbitrary number of unit roots and cointegration relationships (including seasonal unit roots), time-varying local means and drifts, and conditional heteroskedasticity of unknown form and can be used with other identification schemes, including Cholesky and the conventional external IV. We show how to construct pointwise and simultaneous confidence bounds for structural impulse responses and how to compute smoothed local projections with the corresponding confidence bounds. Using simulated data from a standard log-linearized DSGE model, we show that the method can reliably recover the true impulse responses in realistic datasets.
As an empirical application, we adopt the proposed method in order to identify monetary policy shock using the dates of Federal Open Market Committee (FOMC) meetings in a standard six-variable VAR. The robustness of our identification and inference methods allows us to construct an instrumental variable for monetary policy shock that dates back to 1965.
The resulting impulse response functions (IRFs) for all variables align with the classical Cholesky identification scheme and are different from the narrative sign restricted Bayesian VAR estimates. In particular, the response to inflation manifests a price puzzle that is indicative of the cost channel of the interest rates.
Employment history
1) Experience in the organizing committee of the student competition "Olimpiada: I am a professional" in the field of Finance (2017 and 2018). (Letter of Gratitude by the Vice-Rector of the Higher School of Economics. July 2018)
2) I am a part of the expert committee in the field of Economics and Finance in the Open HSE Student Research Paper Competition (NIRS).
3) Member of Academic Council in the Master's program Strategic Corporate Finance
4) Conducting interviews with international students (the Master's program Strategic Corporate Finance)
5) Member of organizing committee of International Research Seminar FES/ICEF.
6) Member of organizing committee of Joint Macro-Finance Online Seminar Series (Bank of Russia, HSE FES/ICEF, NES)
7) Referee experience
FES International Research Seminar
Starting from the 2016-2017 academic year Faculty of Economic Sciences has launched a new international seminar series. The series host many established scholars as well as young promising economists from various respectable universities worldwide.