In this new publication for the Bank for International Settlements, Egemen Eren ’09 and co-authors Stefan Avdjiev and Patrick McGuire review recent events in FX swap markets in the context of the longer-term trends in the demand for dollars from institutional investors.
Since the start of the Covid-19 pandemic, indicators of dollar funding costs in foreign exchange markets have risen sharply, reflecting both demand and supply factors.
The demand for dollar funding has grown in recent years, reflecting the currency hedging needs of corporates and portfolio investors outside the United States.
Against this backdrop, the financial turbulence of recent weeks has crimped the supply of dollar funding from financial intermediaries, sharply lifting indicators of dollar funding costs.
These costs have narrowed after central banks deployed dollar swap lines, but broader policy challenges remain in ensuring that dollar funding markets remain resilient and that central bank liquidity is channelled beyond the banking system.
Opinion piece by Francesco Amodio ’10 (Economics) on Canada’s response to COVID-19 crisis
In a piece published on March 31 in the Montreal Gazette, Francesco Amodio ’10 (Economics) looks at measures taken by the Canadian government in response to the coronavirus pandemic.
Here’s an excerpt:
The measures taken by the Canadian government are in line with those taken in other countries, where governments are adopting either one or the combination of the following two approaches. In the first one, the government lets firms lay off workers, then pays out employment insurance benefits or other kind of income support transfers. The second approach focuses instead on “saving jobs,” with the government subsidizing wages in order to avoid layoffs.
Each approach has its pros and cons. In the short run, the size of wage subsidies and number of potential layoffs will determine which one is costlier. Perhaps more importantly, the two approaches differ in their medium- to long-run impacts.
A displaced worker might rationally prefer to wait through a long spell of unemployment instead of seeking employment at a lower wage in a job he is not trained for. I evaluate this trade-off using micro data on displaced workers. To achieve identification, I exploit the fact that the more a worker has invested in occupation-specific human capital, the more costly it is for him to switch occupations and therefore the higher is his incentive to wait. I find that between 9% and 17% of total unemployment in the United States can be attributed to wait unemployment
Publication in Journal of Banking and Finance by Alex Hodbod (ITFD ’12) and Steffi Huber (Economics ’10, GPEFM ’17)
We have a forthcoming article “Sectoral Risk Weights and Macroprudential Policy” in the Journal of Banking & Finance with our co-author Konstantin Vasilev (Essex).
This paper analyses bank capital requirements in a general equilibrium model by evaluating the implications of different designs of such requirements regarding their impact on the tendency of banks to amplify the business cycle.
We compare the Basel-established Internal Ratings-Based (IRB) approach to risk-weighting assets with an alternative macroprudential approach which sets risk-weights in response to sectoral measures of leverage. The different methods are compared in a crisis scenario, where the crisis originates from the housing market that affects the banking sector and is then transmitted to the wider economy.
We investigate both boom and bust phases of the crisis by simulating an unrealized news shock that leads to a gradual build-up and rapid crash in the economy. Our results suggest that the IRB approach creates procyclicality in regulatory capital requirements and thereby works to amplify both boom and bust phases of the financial cycle. On the other hand, our proposed macroprudential approach to setting risk-weights leads to counter-cyclicality in regulatory capital requirements and thereby attenuates the financial cycle.
Conclusions in brief
We show that IRB risk-weights can induce procyclicality of capital requirements and amplify both boom and bust phases of the business cycle. This is particularly concerning because procyclical risk weights could undermine other macroprudential tools, as these other tools are themselves based on risk-based measures of capital requirements e.g. Counter Cyclical Capital Buffers.
Our alternative approach of macroprudential
risk weights could induce countercyclicality of capital requirements, which may
offer benefits in terms of smoothening financial cycles. Targeting
macroprudential intervention on bank risk-weights is likely to be more
effective when it is sector-specific. This will alter banks’ incentives in a
sensitive way – thereby tending to attenuate sectoral asset booms.
The results complement the ongoing debate about the potential merits of a Sectoral Counter Cyclical Capital Buffer, which is ongoing internationally.
Forthcoming paper in Review of Economics and Statistics by Philipp Ager ’08 and Benedikt Herz ’08 (Economics)
This paper provides new insights on the relationship between structural change and the fertility transition. We exploit the spread of an agricultural pest in the American South in the 1890s as plausibly exogenous variation in agricultural production to establish a causal link between earnings opportunities in agriculture and fertility. Households staying in agriculture reduced fertility because children are a normal good, while households switching to manufacturing reduced fertility because of the higher opportunity costs of raising children. The lower earnings opportunities in agriculture also decreased the value of child labor which increased schooling, consistent with a quantity-quality model of fertility.
Jebb Peria ’10 (Finance), Associate at EV Private Equity
Jebb Peria ’10 recently answered some questions about careers in private equity in a post for his employer, EV Private Equity. Here are a few excerpts from the interview.
I’ve heard of private equity but how does it differ from, say, venture capital or fund management?
Fund management is basically a firm of money managers investing pooled funds from investors. The capital may be invested in traditional asset classes such as equities, fixed income and cash and alternative asset classes such as hedge funds, private equity, real estate, commodities and infrastructure.
Private Equity (PE) is an active form of investment in privately held companies with the objective of growing them over a medium to long-term period. As active investors, PE firms work closely with management to increase and maximise the company’s value through financial engineering, improved governance and operational performance.
At EV Private Equity, we primarily invest in early-growth companies that have: a distinct product or service; the potential to grow rapidly; low levels of debt; and experienced management teams. We seek innovative and disruptive technology companies that can scale and drive superior returns.
Venture Capital (VC) is a subset of PE which provides capital to early-stage businesses, usually in technology-based sectors. Venture capitalists normally invest in high-growth, high-risk, start-up or early-staged ventures, typically with a bias towards technology or innovation. PE tends to focus on later-stage investment in businesses that are more established and are generating cash. VC uses primarily equity while PE may use equity and debt (leverage).
Both PE and VC use a measurement known as MOIC (Multiple On Invested Capital) to calculate the returns they make from their investments. PE target returns range from 2x-5x while VC returns are expected to be higher.
Do I need an MBA from Harvard, a mathematics degree or an accountancy qualification in order to be considered?
No, not necessarily. As a matter of fact, I don’t have any of those credentials. I graduated with a BA in Economics (with highest distinction) from York University in Canada, an MA in Economics from the University of Toronto, and an MSc in Finance from Barcelona GSE. I am also a CFA® charterholder. I guess this depends on which type of PE firm you want to work with as there are generalists and specialists.
As energy specialists, our team at EV Private Equity is comprised of people with substantial experience in the energy industry [oil and gas (O&G), oil field services (OFS)] as well as those from technical disciplines (reservoir, drilling, mechanical, chemical, and software engineering as well as geophysics and naval architecture). We also recruit candidates with graduate business degrees in areas such as MBA, finance, economics, strategy etc.
Is it true that private equity is very secretive and is not accountable to any regulators or governments?
EV Private Equity is regulated by the Financial Conduct Authority in the UK and the SEC in the US under the Investment Advisor Act of 1940.
Like any other firm, EV Private Equity and its portfolio companies are obliged to abide by the laws and regulations of all countries we operate in. This is also part of the fiduciary duty towards the firm’s institutional investors, comprised mainly of large public and private pension funds, insurance companies, university endowment funds and sovereign wealth funds.
What is a typical day like in private equity?
I typically start the morning reading through the latest news and market trends. I skim-through DagensNæringsliv, Bloomberg, Financial Times and even LinkedIn to check on the latest oil price, mergers and acquisitions (M&As) and geopolitical news. Then, I read through my emails to check for any updates on the portfolio companies I’m involved with and any immediate requests from the partners.
My day is normally split between fixed deliveries and ad hoc tasks. My deliveries would range from weekly meetings and operational updates with portfolio companies to monthly, quarterly and yearly financial reporting to updating fair market values of portfolio companies to weekly meetings with the digital marketing team. I would also participate in quarterly investor meetings, board meetings as well as annual strategy meetings with my portfolio companies.
If there’s a deal I am involved in, I would build the financial model, perform valuation and sensitivity analysis and support the drafting of the investment paper. I would also be participating in weekly call updates with the due diligence providers regarding any red flags and show stoppers (in other words, developments that may affect our decision to invest).
If one of my portfolio companies is preparing for an exit, I might be having calls with the management and the financial advisors discussing the potential buyers, the market sentiment and the status of the Information Memorandum (IM), the document we share with prospective buyers.
There is not much slack time. If I do have some spare time, I can always find something to work on: a process to simplify and make more efficient; a model to automate; improvements to our social media presence; or offering support to other office locations.
What are the rewards?
Helping to create value for the company and produce superior returns for investors is rewarding and gratifying.
I also get to work with different partners, management teams, board members and technologies. These teach me different insights, strategies, and management styles.
It is very rewarding to work with the smart, entrepreneurial and down-to-earth group of individuals at EV Private Equity. They make the workplace fun and invigorating.
Of course, the job is also financially rewarding. I would like to believe that I am fairly and reasonably remunerated given my performance and contributions, the skillset I bring to the table, and my dedication to my craft.
Alessandro Franconi ’17 (Macroeconomic Policy and Financial Markets)
“Mini-Bot: Ingenuity or Ignorance” is my first policy brief for the Luiss School of European Political Economy.
“The concept of using mini-BOTs to pay off trade payables may seem like a good idea, but if we analyze it in detail we can intuitively conclude that such a tool is futile and limited…It is clear that the mini-BOTs are a completely sterile, if not harmful, device for public finances, as their implementation (or just the information that the government is officially studying their implementation) would put again Italy on the road to leaving the euro.
Empirical connections between local anti-Muslim hate crimes and international jihadi terror attacks are studied. Based upon rich administrative data from Greater Manchester Police, event studies of ten terror attacks reveal an immediate big spike up in Islamophobic hate crimes and incidents when an attack occurs. In subsequent days, hate crime is amplified by real-time media. It subsequently attenuates, but hate crime incidence cumulates to higher levels than prior to the series of attacks. The overall conclusion is that, even when they reside in places far away from where jihadi terror attacks take place, local Muslim populations face a media magnified likelihood of hate crime victimization following international terror attacks. This matters for community cohesion in places affected by discriminatory hate crime and, from both a policy and research perspective, means that the process of media magnification of hate crime needs to be better understood.
Maryam Rahbaralam ’19 (Data Science) presented “Machine Learning for the Sustainable Management of Main Water Supply Assets” with Jaume Cardús (Aigües de Barcelona) during the Pioneering Fields and Applications (Strong AI) session at the 2019 Big Data and AI Congress in Barcelona.
The developed machine learning model gives the prediction of the probability of failure for each pipe section of the water supply network, allowing an early renewal of those in more detrimental conditions in terms of social, environmental and economic consequences.
Publication in “Journal of Business & Economic Statistics” by
Gergely Ganics ’12 (with A. Inoue and B. Rossi)
In this article, we propose methods to construct confidence intervals for the bias of the two-stage least squares estimator, and the size distortion of the associated Wald test in instrumental variables models with heteroscedasticity and serial correlation. Importantly our framework covers the local projections—instrumental variable model as well. Unlike tests for weak instruments, whose distributions are nonstandard and depend on nuisance parameters that cannot be consistently estimated, the confidence intervals for the strength of identification are straightforward and computationally easy to calculate, as they are obtained from inverting a chi-squared distribution. Furthermore, they provide more information to researchers on instrument strength than the binary decision offered by tests. Monte Carlo simulations show that the confidence intervals have good, albeit conservative, in some cases, small sample coverage. We illustrate the usefulness of the proposed methods in two empirical situations: the estimation of the intertemporal elasticity of substitution in a linearized Euler equation, and government spending multipliers.
Supplementary materials for this article are available online. The online appendix contains the proofs, further theoretical and Monte Carlo results, and the description of the datasets used in the present article. Replication code is available on the journal’s website.
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