master projects – Page 4

Bank Interconnectedness and Monetary Policy Transmission: Evidence from the Euro Area

ITFD master project by Sofia Alvarez, Michael Barczay, Guadalupe Galambos, Ina Sandler, and Rasmus Herløw Schmidt ’19

Editor’s note: This post is part of a series showcasing BSE master projects. The project is a required component of all Master’s programs at the Barcelona School of Economics.

Abstract

Whereas monetary policy in the euro area is conducted by one single authority, the European Central Bank (ECB), the real effects of these decisions provoke different reactions among the set of targeted countries. One common explanation for this finding is structural heterogeneity across the members of the eurozone. The paper assesses how commercial bank interconnectedness – as a specific source of structural heterogeneity – affects the propagation of common monetary policy shocks across the euro countries between 2003 and 2018. While recent research has found that bank interconnectedness can counteract the contraction in loans resulting from a monetary policy tightening in the US, evidence on the effects in the euro area is scarce. The paper tests this hypothesis empirically by constructing a panel data set for the original euro area countries, creating a measure for country-specific bank interconnectedness, and by identifying an exogenous monetary policy shocks based on high-frequency data. Employing local projections we find evidence that – in accordance with the theoretical model we discuss – a contractionary monetary policy surprise leads to a reduction in the supply of corporate and household loans in countries with a low degree of interconnectedness. Conversely, when the banking sector is highly interconnected, the impact of monetary policy is reduced or even counteracted. This implies that a common monetary policy shock can have heterogeneous effects among countries of the euro area, depending on the degree of interconnectedness of their banking industries. These results are robust to the inclusion of a wide set of controls and alternative shock specifications.

Conclusions and Key Results

Standard theory, assuming that the balance sheet transmission channel is at play, suggests that an increase in the interest rate reduces the value of pledgeable assets held by firms and households. This reduction in the borrowers’ creditworthiness consequently induces banks to constrain their amount of lending. A higher degree of interconnectedness of the banking sector, however, makes banks less sensitive to changes in the value of the collateral posted by borrowers since loan portfolios can be traded among banks with diﬀerent risk exposures. Thus, when banks are highly interconnected, the reduction of the loans supply after contractionary monetary policy is expected to be smaller and the effects of monetary policy are likely to be less pronounced.

The paper tests this hypothesis for the eurozone using local projections and a panel dataset of 12 euro-area countries in the period between 2003 and 2018. The eurozone constitutes an excellent subject to study: It exhibits signiﬁcant variation of bank interconnectedness – both across time and countries – which makes the hypothesis of bank interconnectedness as a determinant of heterogeneous reactions to monetary policy particularly relevant.

The key findings of the paper are that interconnectedness is in fact an important driver of heterogeneity in the transmission of monetary policy in the eurozone. More precisely, the analysis shows that when bank interconnectedness is low, contractionary monetary policy leads to a reduction in lending. In countries with highly interconnected banking sectors, however, the paper documents that the impact of monetary policy on loans may be oﬀset. Even more so, our findings suggest that the effect of monetary policy may even be reversed at certain points in time after a monetary policy shock (see Figure 1). More generally, these effects seem to persist for approximately 15 months and hold for both household and corporate loans. A potential conjecture for the observed increase in loans, when bank interconnectedness is high, could be that contractionary shocks induce lending from highly interconnected core countries to countries with low bank interconnectedness in the European periphery.

Additionally, higher interest rates may induce banks to increase the loan supply due to higher potential returns in a context of efficient risk-sharing. The analysis also suggests that cross-country variation of bank interconnectedness, in particular, plays an important role in explaining heterogeneous responses to monetary policy. Muting the cross-country variation, by contrast, delivers eﬀects that are still in line with the theory but which turn out to be statistically insigniﬁcant. In other words, accounting for cross-country heterogeneity is essential. Moreover, employing alternative specifications, the results are found to be robust to using alternative shock measures, including additional controls, and excluding outliers.

Figure_1 — *Figure 1: Impulse response of total loans to a one basis point increase in the monetary policy shock variable (Red: Low bank interconnectedness, blue: high bank interconnectedness)*

Using our estimates to predict the country specific responses to a monetary policy shock, we show that countries are expected to react very heterogeneously. While Greece, for instance, is predicted to experience a contraction of loans after an interest rate hike at its 10th, 50th, and 75th percentile of bank interconnectedness, the effect of monetary policy is almost completely offset in Germany or Austria (see Figure 2).

*Figure 2: Implied heterogeneous responses after 6 months to a common monetary policy shock of 1 basis point by each country’s degrees of interconnectedness*

In sum, the analysis contributes to the understanding of how monetary policy is transmitted across countries in the euro area. The paper shows how heterogeneous responses can be explained by the variation in countries’ individual levels of bank interconnectedness. Furthermore, it provides a potential explanation for why recent research has found rather modest responses of the loan supply to monetary policy. Such observations appear inevitable given that many countries display levels of interconnectedness at which the reaction of loans to monetary policy is predicted to be only small or even nonexistent. Only by incorporating interbank lending into the analysis, sizable effects of monetary policy become apparent again.

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Authors: Sofia Alvarez, Michael Barczay, Guadalupe Galambos, Ina Sandler, and Rasmus Herløw Schmidt

About the BSE Master’s Program in International Trade, Finance, and Development

Estimating Time-Varying Network Effects with Application to Portfolio Allocation

Finance master project by Daniel A. Landau and Gabriel L. Ramos ’19

Editor’s note: This post is part of a series showcasing BSE master projects. The project is a required component of all Master’s programs at the Barcelona School of Economics.

Abstract

In this paper, we characterize a variety of international financial markets as partially correlated networks of stock returns via the implementation of the joint sparse regression estimation techniques of Peng et al. (2009). We explore a number of mean-variance portfolios, with the aim of enhancing out-of-sample portfolio performance by uncovering the hidden network dynamics of optimal portfolio allocation. We find that Markowitz portfolios generally dissuade the inclusion of central stocks in the network, yet the interaction of a stock’s individual and systemic performance is more complex. This motivates us to explore the time-varying correlation of these topological features, which we find are highly market dependent. Building on the work of Peralta & Zareei (2016), we implement a number of investment strategies aimed at simplifying the portfolio selection process by allocating wealth to a targeted subset of stocks, contingent on the time-varying network dynamics. We find that applying mean-variance allocation to a restricted sample of stocks with daily portfolio re-balancing can statistically signiﬁcantly enhance out-of-sample portfolio performance in comparison to a market benchmark. We also find evidence that such portfolios are more resilient during periods of major macroeconomic instability, with the results applicable to both developed and emerging markets.

Conclusion and Future Research

In our work, we represent 4 international exchanges as individual networks of partially correlated stock returns. To do so, we build a Graph, comprised of a set of Vertices and Edges, via the implementation of the joint sparse regression estimation techniques of Peng et. al (2009). This approach allows us to uncover some of the hidden topological features of a series of Markowitz tangency portfolios. We generally find that investing according to MPT dissuades the inclusion of highly central stocks in an optimally designed portfolio, hence keeping portfolio variances under control. We find that this result is market-dependent and more prevalent for certain countries than for others. From this cross-sectional network analysis, we learn that the interaction between a stock’s individual performance (Sharpe ratio) and systemic performance (eigenvector centrality) can be complex. This motivates us to explore the time-varying correlation ρ between Sharpe ratio and eigencentrality.

Optimal_Weights_for_Tangency_Portfolio_Strategy — Optimal Weights for Tangency Portfolio Strategy.

Overall, we show that in considering the time-varying nature of partially correlated networks, we can enhance out-of-sample performance by simplifying the portfolio selection process and investing in a targeted subset of stocks. We also find that our work proposes a number of future research questions. Although we implement short-sale constraints, it would also be wise to introduce limits on the amount of wealth that can go into purchasing stocks, as this would help to avoid large portfolio variances. Furthermore, our work paves the way for future research into the ability of ρ-dependent investment strategies to enhance portfolio performance in times of macroeconomic distress and major financial crises.

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Authors: Daniel A. Landau and Gabriel L. Ramos

About the Barcelona GSE Master’s Program in Finance

Certain uncertainty? The response of Venezuelan banks to a political dilemma

Economics of Public Policy master project by Mary Armijos and Guillem Cuberta ’19

Editor’s note: This post is part of a series showcasing BSE master projects. The project is a required component of all Master’s programs at the Barcelona School of Economics.

Introduction

Our work focuses on the analysis of the Venezuelan banks, which have become more vulnerable. The leading causes of this vulnerability have been oil price shocks, political instability, pro-cyclical monetary conditions (i.e., interest rates), low level of financial intermediation, changing structure (e.g., consolidation, closure or nationalization), non-traditional bank transactions, high exposure to the public sector, and government intervention in their operations. (Blavy R., 2014) Hence, studying the response of banks to policy uncertainty becomes relevant. However, even more critical, in Venezuela’s context, would be to ask: do banks respond differently to uncertainty if they are politically connected?

To address this question, we construct two indices: the policy uncertainty index and political connection index. Our uncertainty index is in a monthly basis and bank-invariant; it is developed following the work previously done by Baker, Bloom, and David, on the Economic Policy Uncertainty Index (EPU Index) and by Ahir, Bloom, and Furceri, on the World Uncertainty Index (an extension of the EPU). Similar to Xu and Zhou (2008), for the case of the political connection index, we define the dummy variable connected bank equal one based on whether it is a state-owned bank. Alternatively, in case it is a private one if at least one of the board members has any connection with someone from the government. We adapt these criteria to the information there is available from Venezuela. We also look if one of the members is part of the ‘bolibourgeoisie’ ( a combination of the words Bolivarian and bourgeoisie, a term used to classify the businessmen and public officials linked to the government). For our dependent and micro-control variables (i.e., bank characteristics), we use monthly data from 2006 to 2018 obtained from SUDEBAN (Venezuela’s Superintendence of Banks). Moreover, for the macro-control variables, we obtain monthly data from the International Financial Statistics of the International Monetary Fund (IMF). The variables we choose for our specifications are based on the works done by Vera et al. (2019) and Bordo et al. (2016).

Our central hypothesis is that when there is high policy uncertainty, political connections may allow connected banks to smooth the effects of uncertainty. We believe that connected banks might respond differently to uncertainty because they have privileged information or preferential treatment from the government, which grants them a competitive advantage over non-connected banks. To test the response of banks, we look at their behavior respect to credit supply and provisions, and we also investigate banks’ profitability in periods of uncertainty through the ROA. Our identification strategy to investigate the causal effect of policy uncertainty and political connection considers the fact that the uncertainty index is a high-frequency time series, which makes it be almost an exogenous variable. Also, the political connection index is not endogenous as it does not vary over time.

In addition to that, we control for bank-invariant and time-specific factors that affect both the right-hand side and left-hand-side variables by adding bank and time fixed effects. Furthermore, to separate the impact of our primary explanatory variable (interaction) from other confounding factors, we control for a block of bank-specific covariates. We also consider different specifications with and without lags of these controls to mitigate the potential reverse-causality concern. Even though we know that all of these adjustments might not entirely correct for omitted variable bias, we consider it adjusts well enough to investigate this relationship. We consider that one of the significant sources of potential bias comes from monthly macro changes (i.e., exogenous shocks like oil prices or U.S. sanctions, and government decisions) that are accounted by including time fixed-effects.

**Figure 1**: Monthly Economic Policy Uncertainty Index for Venezuela (EPUV)

Results

In our main results, we find that politically connected banks acquire more risks when there is higher uncertainty as an increase of 10 percent in our uncertainty measure leads them to give on average, 0.0262 percent more credits than non-politically connected banks. This result corroborates similar results from the literature that establishes a positive value from being politically connected (Kostovetsky 2015). Also, we observe that an increase in the uncertainty index induces politically connected banks to hold more loss provisions in their portfolio than non-politically connected banks. A 10 percent increase in our uncertainty index prompts politically connected banks to hold 0.0192 percent more loss provisions than non-politically connected banks. Lastly, the effect of economic policy uncertainty for politically connected banks on ROA has a positive sign. A 10 percent increase in uncertainty increases the average returns on assets of politically connected banks by almost 11 percent compared to non-politically connected banks.

Summing up, connected banks can give more credit to the public in periods of higher uncertainty, at the same time that they hold more loss provisions. The first result is consistent with the ones shown by Cheng et al. (2017), where they find that banks supply much more credit when there is high uncertainty. However, our result of provisions does not coincide with theirs. Contrarily, they find that under higher uncertainty, connected banks reserve lower provisions than unconnected banks. In the case of the profitability analysis, connected banks have lower profits when there is high uncertainty. These results go along with the ones found by Dicko (2016).

We consider that this study presents new relevant findings regarding the literature of political connection and policy uncertainty, and for the Venezuelan economy overall. The political connection matters in periods of high uncertainty but until one point. From our results, we find that politically connected banks seem pro-risk as they give more credit when there is more policy uncertainty. However, on another level, it appears that they do receive privilege information form the government (bad news about the future) that makes them risk-averse at the same time as they also reserve more provisions. Additionally, the result of the relationship between uncertainty and profitability indicators, like ROA, indicates that being politically connected might not be extremely helpful to banks if they only benefit from having more information and do not receive any tangible benefit from the government. For further studies, it would be interesting to analyze how economic agents respond to policy uncertainty depending on the type of benefit they receive from being politically connected to some institutions.

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About the BSE Master’s Program in Economics of Public Policy

The Impact of Non-contributory Pensions. A Case Study for Costa Rica

Economics of Public Policy master project by Hazel Elizondo, Sandra Flores and Alicia de Quinto ’18

Editor’s note: This post is part of a series showcasing Barcelona GSE master projects by students in the Class of 2018. The project is a required component of every master program.

Authors:

Hazel Elizondo, Sandra Flores and Alicia de Quinto

Master’s Program:

Economics of Public Policy

Paper Abstract:

Even when only 20% of the elder population in the world receives pension coverage (Pallares-Miralles, Romero and Whitehouse, 2012) which in addition is not always adequate according to ILO, non-contributory pensions are present only in a handful of developing countries. Moreover, the elderly population is currently growing as individuals tend to live longer, what further evidences the imperative need to apply this type of programs. Costa Rica implemented a non-contributory pension policy in 1975 to ensure the livelihood of those in economic need that were not able to save provisionary funds to confront the old age risks, so that elders aged above 65 living in extreme poverty are eligible for coverage. Additionally, Costa Rica adopted a 186% increase on the pension amount in 2007 in order to mitigate poverty. This study aims to provide further empirical evidence of the indirect effects of the non-contributory pensions in Latin America, through a study case for Costa Rica that explores the impact of this pension on employment and schooling, household composition, and changes in well-being for the period from 2001 to 2009.

Figure: Poverty rate for different age ranges in Costa Rica

The methodology applied includes a first difference-in-differences specification (DD) as a general model, which compares the group of receivers before and after 2007 with a control group aged above 65 years old. Secondly, we exploit the discontinuity on the treatment assignment regarding the age of the oldest household member to define a Regression Discontinuity Fuzzy Design (RD). This local analysis only identifies the effects of receiving the pension, so that we move towards a third Difference in Discontinuity Design (diff-in-disc) that combines the previous models, quantifying the impacts of the pension increase as well. The RD and diff-in-disc settings include an alternative sample where the treated are households with a member between 65 and 69 years, while the counterpart is aged between 61 and 64.

Conclusions and key results:

Our results show a generally positive picture of the Costa Rican non-contributory pension, if we consider that the policy was designed to provide an allowance to elder that never contributed to the formal system, allowing them to retire at age 65. However, conditional income transfers sometimes involve unintended consequences that characterize the policy as defective.

Table: Main Results

In the case of the DD sample, where the family structures are characterized by households with senior members and households where the recipient is father or mother of the household head, the results show major spillover effects on the remaining members, especially in terms of labor- related reactions. Indeed, the estimations show that those households that benefit from the non- contributory pension reduce significantly by 0.179 the number of individuals in the labor force, compared to non-beneficiaries. Individuals in the treated households work 1.747 hours less than their counterparts and receive a labor income 61.9 USD lower than those households that do not receive the pension. Given that the Costa Rican non-contributory pension policy requires leaving the labor market as a necessary condition for receiving the grant, we might relate the reduction in labor participation to perverse incentives, as the remaining household members might take advantage of this transfer to change their time allocation preferences between work and leisure.

Nonetheless, the results obtained in the RD and diff-in-diff models rule out our preliminary interpretation. Both estimates reveal no significant reactions at the household level for any of the outcomes analyzed, what means that households do not change their employment-related decisions in the short-run, even when the recipient must leave the labor market. In this case, the households with senior members predominate over other type of family structures, hence we would have expected a significant decreasing effect for labor force participation. Probably this is because unemployment and job instability hit the most vulnerable population groups, so that individuals with uncertain job prospects see in the non-contributory pension an opportunity to receive a steady income. Moreover, we do not find evidence neither for the incentive for other young members of the family to move in with the elderly participant, nor for the recipient to move out and live on her own.

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More about the Economics of Public Policy Program at the Barcelona Graduate School of Economics

Investigation of Sentiment Importance on Intraday Stock Returns

Data Science master project by Michele Costa, Alessandro De Sanctis, Laurits Marschall and S. Hamed Mirsadeghi ’18

Editor’s note: This post is part of a series showcasing Barcelona GSE master projects by students in the Class of 2018. The project is a required component of every master program.

Authors:

Michele Costa, Alessandro De Sanctis, Laurits Marschall and S. Hamed Mirsadeghi

Master’s Program:

Data Science

Paper Abstract:

The main goal of our Master Project is to predict intraday stock market movements using two different kinds of input features: financial indicators and sentiments from news and tweets. While the former are part of the common technical analysis of financial econometric models, the extracted sentiment of news articles and tweets from Twitter are also proven to correlate with stock markets movements. Our paper aims at contributing to the existing academic and professional knowledge in two main directions. First, we evaluate three different approaches to extract the sentiment from both social and mass media based on its forecasting power. Second, we deploy a battery of engineered features based on the sentiment, together with the financial indicators, in a machine learning model for a fine-grained minute-level forecasting exercise. In the end, two different classes of models are fitted to test the forecasting power of the combined input features. We estimated a classical ARIMA-model, and an XGBoost-model as machine learning algorithm. We collected data on the companies Apple, JPMorgan Chase, Exxon Mobil, and Boeing.

Figure: Exxon Mobil — The picture shows how sentiments towards Exxon Mobil moved over time. The two lines refers to two different methodologies: Loughran-McDonald is based on a financial dictionary while SentiStrength was trained on social media such as MySpace.

More about the Data Science Program at the Barcelona Graduate School of Economics

Option Pricing in the Heston Stochastic Volatility Model: An Empirical Evaluation

Master project by Patrick Altmeyer, Jacob Daniel Grapendal, Makar Pravosud, and Gand Derry Quintana ’18

Editor’s note: This post is part of a series showcasing Barcelona GSE master projects by students in the Class of 2018. The project is a required component of every master program.

Authors:

Patrick Altmeyer, Jacob Daniel Grapendal, Makar Pravosud, and Gand Derry Quintana

Master’s Program:

Finance

Paper Abstract:

There exists a substantial body of literature concerned with the calibration of the Heston model for pricing financial derivatives under stochastic volatility, many of which rely on computationally expensive algorithms. Our paper evaluates a calibration method of the Heston model proposed by Alòs, De Santiago, and Vives (2015), which can be used to price derivatives with little computational effort. The calibration method is innovative in the sense that it considers only the three most critical regions of the implied volatility surface. The regions where the underlying option is, firstly, at-the-money, secondly, close to maturity and lastly, far away from maturity. Although their procedure is parsimonious and very easy to implement, they calibrate a model whose empirical applicability is contested.

The main contribution of our paper is the evaluation of their model in an extensive numerical exercise as well as an application to real data. Collecting empirical option data has been one of the main challenges with respect to this work, since historical data on financial derivatives is not accessible to the public. Faced with this issue we have written a script that allowed us to automatically scrape option data at a high frequency over just a couple of weeks. Thus, we build our own extensive data base. Also, we have made the data and code available on https://griipen.shinyapps.io/bgse/ and https://github.com/HitKnit/BGSE2018/tree/HitKnit-optionscraping, respectively.

In terms of our results, we find that whilst the calibration method has solid theoretical foundations and produces satisfactory estimation results within the theoretical Heston universe. However, it fails in practice. Specifically, for the numerical exercise we find that out of all simulations the maximum average error across the entire volatility surface is 0.999 percent while the mean error across simulations is only 0.481 percent. In sharp contrast to that, absolute percentage errors for our empirical data are on the order of 30-40 percent in many cases. In the following figure, we present our findings for intra-daily data from May 16, 2018. The left column shows empirical implied volatilities for a European call option on Facebook Inc. (FB) stocks. From top to bottom volatilities are shown for the opening, lunch and closing sessions. The central column shows the fitted volatility surfaces while the right column shows absolute percentage differences between empirical and estimated values. The finding that errors are particularly high for at-the-money options with short times to maturity is robust across the entire data sample.

Conclusions and key results:

In light of these results, we conclude that inherent limitations of the Heston Model disqualify the calibration for practical use. Nonetheless, we believe that similarly simple calibration methods as the one examined here should be used in combination with more sophisticated option pricing models.

References:

Alòs, Elisa, Rafael De Santiago, and Josep Vives. 2015. “Calibration of Stochastic Volatility Models via Second-Order Approximation: The Heston Case.” International Journal of Theoretical and Applied Finance 18 (06). World Scientific: 1550036.

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More about the Finance Program at the Barcelona Graduate School of Economics

The Impact of a Cash Transfer Program on Life Outcomes: Evidence from Uruguay

Economics of Public Policy master project by Karina Colombo, Gabrielle Lohner, and Eric Ramirez-Diaz ’18

Editor’s note: This post is part of a series showcasing Barcelona GSE master projects by students in the Class of 2018. The project is a required component of every master program.

Authors

Karina Colombo, Gabrielle Lohner, and Eric Ramirez-Diaz

Master’s Program

Economics of Public Policy

Paper Abstract

Our paper analyzes the impact of a cash transfer program targeting households in extreme poverty in Uruguay, called the Tarjeta Uruguay Social (henceforth referred to as TUS). In the past decades, cash transfers have become one of the main social assistance policies used to address poverty and inequality in developing countries. Their objective is to reduce vulnerability by increasing and smoothing household income, although additional objectives are usually defined depending on the program and country, such as increasing access to health and education, and reducing food insecurity (DFID 2011; Honorati et al. 2015).

The impact of these programs on different life outcomes has been widely studied. Overall, positive impacts on poverty, food insecurity, child school enrollment, labor outcomes, health and social cohesion have been found (DFID 2011; ODI 2016). Nevertheless, more research is still needed to understand the channels and particular aspects that determine their success, since countries differ widely in the details of program design. In our research, by taking advantage of considerable design modifications since the implementation of TUS, we evaluate the impact of the amount of the transfer and the benefit duration on relevant outcomes.

The Tarjeta Uruguay Social (TUS) is a conditional cash transfer program implemented in 2009 which aims at assisting those in situations of extreme poverty in Uruguay. It targets the 60,000 worst-off households by providing them with a monthly cash transfer on a prepaid magnetic card. This card can be used to purchase food items, cleaning supplies, and hygiene products, excluding cigarettes and alcohol. Eligibility for the program is based on the Critical Needs Index (CNI), a proxy means test that evaluates household poverty, using variables associated to education, dwelling, access to durable goods and household composition. The program has undergone many modifications since its inception, including increasing the number of participants, changing the eligibility criteria, and a doubling of the benefit for half of the recipients. Our analysis begins in 2013, in which the program had 60,000 participants, and the poorest 30,000 according to the CNI received a doubling of their benefit, creating two benefit categories: Simple TUS and Double TUS. In our research, we exploit the doubling of the benefit based on the CNI by using a Fuzzy Regression Discontinuity Design to evaluate the impact of the amount of the benefit on life outcomes.

The availability of an extensive set of administrative data allowed us to evaluate the impact of the doubling on an array of outcomes. There are many different channels through which this cash transfer program could have positive effects, since the resources freed up by the relaxation of the household budget constraint could be used differently according to household preferences. Therefore, by taking advantage of a rich set of administrative data, we analyzed 65 outcomes: housing and living conditions, food insecurity, formal labor market work, education enrollment of children and adolescents, prenatal and birth health conditions, and family composition. Additionally, we analyze how the duration of the benefit affects the impact of the program by comparing the effects for beneficiaries who receive the transfer for different time periods. We analyze short-term outcomes for those who receive the transfer for less than a year; medium-term outcomes for those who receive the transfer for two to three years; and long-term outcomes for those who receive the transfer consistently for three years.

Conclusions

Probability of Receiving Double TUS According to Distance from Eligibility Threshold by Month, 2013. Analysis begins in May 2013.

Our results show than an increase in the amount of a cash transfer can in fact have important impacts on the life outcomes of recipients. Positive effects were found with regard to living conditions, with an increase in investment in durable goods and a betterment of housing conditions, such as purchasing water heaters or washing machines, adding a bathroom to the home, and upgrading from a trash roof to a concrete one. Additionally, results show positive impacts concerning individual outcomes, with improvements regarding prenatal care and months of formal work observed. Nevertheless, some negative results were found in the short-term, which could potentially be explained by an attempt of manipulation by the beneficiaries in order to ensure continued benefit provision under uncertainty. Results also show that the duration of the benefit has a considerable impact on how the transfer is spent. More positive significant household results are found in the medium-term, while individual results become stronger in the long-term. The increasing effects of more persistent benefits could potentially be explained due to uncertainty in the short-term regarding whether the benefit will continue to be provided, which decreases over time.

This study contributes to the literature of poverty alleviation policies by providing evidence which can be used to improve the design of cash transfer programs. The positive effects found in this paper from comparing different amounts of the transfer within the same program indicate that the monetary amount of the benefit is a relevant policy parameter with consequences for the effectiveness of the program. Additionally, the results for heterogeneous effects by benefit duration indicate that the persistence of the transfer is another relevant aspect of program design. The evidence provided in this paper indicates that a predefined duration upon entering the program together with a minimum duration of one year could constitute a good practice. This may mitigate negative effects regarding household manipulation attempts and potentiate positive effects by reducing income volatility and increasing housing investments. Our results suggest that further research on benefit size and timing is imperative for policy design of cash transfers, one of the main tools to reach universal social protection.

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More about the EPP Program at the Barcelona Graduate School of Economics

Labor Markets, Search Frictions and International Trade: Assessing the China Shock

Master project by Marcos Mac Mullen ’18

Editor’s note: This post is part of a series showcasing Barcelona GSE master projects by students in the Class of 2018. The project is a required component of every master program.

Authors:

Marcos Mac Mullen

Master’s Program:

Macroeconomic Policy and Financial Markets

Paper Abstract:

The goal of this paper is to assess quantitatively the impact that the emergence of China in the international markets during the 1990s had on the U.S. economy (i.e. the so-called China Shock). To do so, I build a model with two sectors producing two final goods, each of them using as the only input of production an intermediate good specific to each sector. Final goods are produced in a perfectly competitive environment. The intermediate goods are produced in a frictional environment with labor as the only input. First I calibrate the close economy model to match some salient stylized facts from the 1980s in the U.S. Then to assess the China Shock I introduce a new country (China) in the international scene. I proceed with two calibration strategies: (i) calibrate China such that it matches the variation in the price of imports relative to the price of exports for the U.S. between the average of the 1980s and the average of 2005-2007, (ii) Calibrate China such that variation in allocations are close to the ones observed in data, for the same window of time. I found that under calibration (i) the China Shock in the model explains 26.38% of the variation in the share of employment in the manufacturing sector, 16.28% of the variation in the share of manufacturing production and 27.40% of the variation in the share of wages of the manufacturing sector. Finally, under calibration (ii) I found that the change in relative price needed to match between 80 to 90 percent of the variation in allocations is around 3.47 times the one observed in data.

Conclusions and key results:

According to the model, the China Shock explains 26.35% of the variation in the share of manufacture employment, 16.28% of the variation in the share of manufacturing production and 27.44% of the variation in the share of wages of the manufacturing sector. The first of these results is consistent with findings in Autor et al. (2013). On the other hand, the variation in the unemployment rate of the economy is not matched, neither for the first nor the second calibration of the open economy. I also found that as a consequence of the China Shock, real wages increase when measuring them in terms of the price of the import good, and decrease when measured in terms of the price of the export good. This result is not in line with findings in Autor et al. (2013). The optimal unemployment insurance in the open economy is 6.13% of average wages higher than in the close economy because the unemployment rate of the open economy is higher than in the close economy (0.9% difference). Finally, the model generates a non-traditional source of comparative advantage, arising from differences in the relative bargaining power of workers.

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More about the Macro Program at the Barcelona Graduate School of Economics

The Effects of the South African Minimum Wage on Labour Market Outcomes for Low-Income Earners

Master project by Samuel Jones, Annanya Mahajan, Maria Oliva, Debora Reyna, Marta Vila

Editor’s note: This post is part of a series showcasing Barcelona GSE master projects by students in the Class of 2018. The project is a required component of every master program.

Authors:

Samuel Jones, Annanya Mahajan, Maria Oliva, Debora Reyna, Marta Vila

Master’s Program:

International Trade, Finance, and Development Program

Paper Abstract:

We capitalise on the 2006 implementation of a minimum wage for the hospitality sector to make well-evidenced inferences about the impact of the upcoming National Minimum Wage (NMW) Legislation on low-wage workers. Our paper focuses on the two largest low-wage sectors currently without minimum wage regulation, which are manufacturing and construction. Two regression specifications and sensitivity analysis are used to provide insights into the implication for wages, hours worked, employment, formality and poverty rates. In light of our results and a comprehensive review of the literature, we conclude that the NMW will be largely beneficial for low-wage labourers. Our critical recommendation for policymakers is the need for complementary policies to ensure compliance and facilitate the transition of vulnerable groups (particularly black women) into the formal sector.

Conclusions and key results:

From our first specification, our analysis suggests that wages and hours worked will increase in manufacturing and construction sectors as a result of the minimum wage, mostly driven by increases for black and female workers. Although the policy is likely to increase the formality rate among male workers, we predict formality will fall among females as employers try to circumvent the legislation. Therefore it is crucial that adequate complementary policies are implemented to ensure the benefits are captured by all population groups. Our second specification exploits the variation in the median wage across provinces. In doing so, we find no significant effect on wages, which signals regional impacts of the minimum wage are fairly homogeneous. Therefore, compared to other countries adopting a similar policy, the implementation of safety-nets combating the adverse effects of the minimum wage will be relatively more straightforward. By conducting sensitivity analysis around compliance rates and poverty lines already stipulated in the literature, we predict between 100,000 and 300,000 manufacturing and construction workers will be lifted out of wage poverty as a result of the minimum wage. We combine our empirical partial equilibrium analysis with theoretical general equilibrium forces to provide statements on the anticipated lower bound of wage changes.

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The dynamic relationship between long term interest rates and fiscal stances in the EMU

Editor’s note: This post is part of a series showcasing Barcelona GSE master projects by students in the Class of 2018. The project is a required component of every master program.

Authors:

Sybrand Brekelmans, Guillermo Sanz Marin, and Luca Tomassetti

Master’s Program:

Macroeconomic Policy and Financial Markets

Paper Abstract:

In this paper we study the dynamics and drivers of 10 year’s sovereign bond yields using a panel of the original 11 Eurozone countries (excluding Luxembourg). The interest of this study relies on the fact that despite very different macroeconomic policy stances in the variables that we believe determine interest rates among these countries, 10 years Eurozone bond yields almost perfectly converged during the 2000’s, before they suffered a sudden disconnection in the aftermath of the Great Financial Crisis.

To this end, we apply two different methodologies. A Panel Data approach (that we end discarding) and a Time Varying Coefficients model using the Kalman Filter, which allows us for capturing changes in the pricing mechanism of bond yields over time. Initially, by using the latter methodology without controlling for the volatility of the interest rates (which dramatically increased after 2008), we obtain very noisy results that are barely explainable, since the coefficients seem to be capturing these changes in volatility. Once we introduce in the filter a GARCH process for the variance-covariance matrix of the interest rates that we use in the Time Varying Coefficients approach, we manage to obtain much more meaningful and explicative results.

One of our key contributions is the inclusion of new fiscal and macroeconomic variables as determinants of yields in the different Eurozone countries, which were discarded by other studies in the field. We also contribute by controlling by common determinants to all the Eurozone countries, which we obtained by applying a common component approach. Furthermore, our findings confirm that after the period of divergence in interest rates, started in the aftermath of the Great Financial Crisis, and caused by a refocus on fundamentals, Eurozone interest rates have converged again under the effect of a normalization of bond yield drivers, similarly to their pre-crisis levels, although not to the same extent. Another implication that we find is that in times of economic uncertainty and financial hysteresis, when default risk becomes an issue, the effects of government policy on interest rates can significantly lead to accentuated crowding out effects.

Conclusions and key results:

Our work indicates that there has been a significant break in the way sovereign debt was priced after the Great Financial Crisis of 2008, indicating a return to fundamentals as main drivers of sovereign yields. We find that several factors reflective of fiscal and macroeconomic stances became increasingly important during the crisis, after having been ignored in previous years. As such, Debt to GDP, Deficit to GDP, GDP growth and Current Account balances to GDP, among others, started to play important roles in the determination of long term interest rates for Eurozone government bonds. In line with previous research, our findings confirm the existence of 3 distinct phases in the euro bond market. A period of high integration, a period of disintegration, and a phase of partial reintegration (Adam and Lo Duca (2017)).

Our findings suggest that during periods of economic uncertainty characterized by high volatility in the financial markets, investors tend to focus on fundamentals, while in times of economic boom they do not discriminate too much among the different stance of these macroeconomic determinants. This finding has important policy implications since it suggests that during economic crises interest rates react much more to unsustainable fiscal policies and macroeconomic imbalances than during calmer times, causing a great private sector crowding out effect (Laubach (2011)).

Therefore, our results suggest that governments should pay closer attention to their fiscal stances during times of economic turbulence in order to avoid the detrimental effects of high interest rates on activity in a period of economic agent´s lack of confidence. As argued before by De Grauwe and Ji (2013), this former effect is exacerbated by the fact that Eurozone governments have no control over monetary policy, making impossible for them to reduce interest rates by no other means than sound fiscal policies. In line with this result, we notice that the ECB’s unconventional monetary policy (we obtain that the impact of short term interest rates -one of our common determinants obtained by principal components- on long yields has diminished over time) helped to bring down European bond yields after 2014. This fact contributed to put the fiscal stances of these countries, and other essential macroeconomic variables, back to sustainable levels, that along with the structural reforms carried out (which in addition to the former effect, have also contributed to bring back economic confidence and dynamism) have had by its own another loosening impact in the interest rates that these countries have been facing in every debt issuance.

Regarding the methodologies used to address our research question, we were able to obtain robust results and determine which method was the most appropriate to investigate the drivers of 10 year’s sovereign bond yields. We found that panel data approaches, which are widely used in the literature, lead to unstable and unsatisfactory results, causing us to attach limited credibility to the outcomes of such analysis. However, the Time Varying Coefficients approach seems more reliable and yields more robust and plausible results after we model the changes in volatility appropriately. We believe that having a larger sample (we use the forecasts released twice a year by the IMF in its World Economic Outlook and by the OECD in their Economic Outlook in order to control by the effect of the market´s forward looking in current levels of interest rates, as well as by reverse causality) would have allowed us to obtain more reliable results on this approach as well.

A suggestion for further research would be to apply Bayesian techniques to estimate our model. Indeed, given the limited amount of data available and the complexity of our models, these methods seem to suit better in this kind of estimation, where the great amount of parameters, as well as the possible presence of non-linearities, can make the optimization process very costly. Consequently, this methodology would have allowed us to also model the variance of the Time Varying Parameters, and not only the ones of the interest rates (our observables) with another GARCH or stochastic volatility process, since we expect that these variances could also follow a conditional process, which might have an impact on our estimation results.

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More about the Macro Program at the Barcelona Graduate School of Economics