Theses - Economics

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Open Access
Essays on Production Structure and Economic Integration
Smitkova, Lidia
In this dissertation, I present three chapters that study the linkages between the structural makeup of economies and the process of trade- and financial liberalization. In the first chapter I examine the role of trade and external deficits in explaining the patterns of structural change in twenty developed and developing economies between 1965 and 2000. First, for each country, I break down the time series of manufacturing value added share into a secular trend and a trade-induced deviation from the trend. I show that national differences are in large part due to trade. Second, I investigate changes in sectoral productivity, trade costs and trade deficits as the driving forces behind the patterns in the data. To do this I build a multi-sector Eaton and Kortum (2002) model and simulate the effects of different shocks on the manufacturing value added shares in the sample. While calibrating the model, I develop a novel method of identifying trade cost- and productivity shocks, which makes use of symmetry restrictions on sectoral trade cost shocks. I calibrate the model at a two-digit level of disaggregation, which permits me to study not only the changes in the manufacturing share, but also its composition at a sub-sectoral level. I find that open economy forces are responsible for 32% of the observed change in the manufacturing shares in my sample, and for 39% if the composition of the manufacturing sector is taken into account. Focusing on individual shocks, I show that for the aggregate manufacturing share, trade cost- and aggregate trade deficit shocks played the biggest role, whereas the productivity shocks mattered more in driving the composition of manufacturing. In the second chapter, I study financial liberalization between economies that differ in their overall competitiveness. I first show that if firms compete oligopolistically, then competitiveness --- relatively low aggregate unit costs of production --- is a feature of an economy with a fatter tailed productivity distribution and relatively more very large --- `superstar’ --- firms. Embedding this setup in a two-country model with heterogeneous agents and non-homothetic saving behaviour, I show that if the home is more competitive, then: (1) it enjoys a higher aggregate profit rate than foreign; (2) its autarkic interest rate is lower than that in foreign; (3) should the two economies undergo financial liberalization, the capital will be flowing from home to foreign; (4) if one of the sectors is non-tradable, the capital inflows push up the wages in foreign, leading to further losses of competitiveness and to current account overshooting. In the third chapter, I calibrate the quantitative version of the model developed in Chapter 2 to eight European economies on the eve of the Global Financial Crisis. I show that the competitiveness gap can explain 27% of variation in the current account imbalances incurred in the period. I conclude by discussing policies for rebalancing.
Open Access
Essays on the behaviour of political and financial markets
Auld, Thomas
This thesis considers the behaviour and relationships between financial and prediction markets around elections. We begin by reviewing the literature. There are many small studies of individual elections and events, particularly of the 2016 UK European Union referendum. However, no studies that consider multiple events, nor present theories that apply in a general setting, are found. We believe this is a gap in the literature. Chapter 1 begins with a study of the Brexit referendum. Using a flexible prior and Bayesian updating, we demonstrate a major violation of semi-strong market efficiency in both the betting and currency markets on the night following the vote. It appears that it took a full three hours for prices to reflect the information contained in the publicly available results of the referendum. Chapter 2 presents a model linking the prices of financial and binary options in the prediction markets in the overnight session following an election. Starting from basic assumptions we find that prices in both markets should be cointegrated. Under risk neutrality the relationship is linear. However, departures from this assumption result in a non-linear cointegrating relationship. We test the theory on three recent elections. Strong support for the theory is found for two events. The linear cointegrating model fits the data from the night of the EU referendum remarkably well. However, departures from risk neutrality are needed to explain the behaviour observed on the night of the 2016 US presidential election. Chapter 3 considers pricing relationships in the weeks and months leading up to an election. Again using economic assumptions, we derive a relationship between asset price returns and changes in the prices of betting market binary options linked to an election result. This model is extended to equities using the ubiquitous Fama–French 5 factor model. The result is a 6 factor characteristic model, where the additional factor is related to political risk. We test the model on six recent elections. Using daily data, strong support is found for the theory for four events and weak evidence for one. The remaining election does not appear to be informative for asset prices. Interesting relationships are also uncovered between firm characteristics and political sensitivity. This is achieved by exploring the political factor loadings of the different equities under study. The main contributions of this thesis are, one, using a flexible Bayesian approach to demonstrate that, without a shadow of a doubt, any `bubble’ in opinion for remain continued well into the night of the EU referendum, and two, presenting pricing models of prediction and financial markets that apply in general settings and have strong support in the data. We also show that on nights after elections, betting markets lead financial markets on the scale of minutes to tens of minutes. This is consistent with, and an extension of, the conclusion of the existing literature that prediction markets have superior forecasting ability. Whether or not this lead–lag relationship occurs at other times prior to political events is an open research question.
Open Access
Essays on Networks and Industrial Organization
Kalbfuss, Joerg
Chapter I: Cohesive Anarchy --- In a conflict, a small force may overcome a larger one if the latter fails to coordinate. To understand how incentives drive such failures, I study Tullock contests between a cohesive faction and a group embedded in a network. The group’s strength equals the sum of its members' efforts, where links measure their pairwise complementarity or interference. I characterize equilibria for general networks, and find only few members are likely to contribute. Furthermore, the prize and a network measure of interconnectedness jointly improve the internalization of spillovers by the group, so its performance varies with the stakes -- escalation induces cohesion. Chapter II: Spectral Oligopolies --- We study how demand interactions incentivize multiproduct oligopolists to reduce their variable production costs. Our starting point is an equivalence between multimarket competition over dependent products and single-market competition over independent bundles from which we derive three insights. First, heterogeneous innovativeness begets a core-fringe separation. While strong innovators dominate clusters of complementary markets through demand-side economies of scope, others retreat towards niches whose isolation attenuates the impact of investments. Second, the translation from innovative advantage into profits is strongest in `contractor' graphs, the antipodes of expanders. These graphs comprise clusters which are densely linked within but scarcely without, yet synergize well both by themselves as well as collectively. Consequently, the parts and the whole make for attractive and relatively independent investment targets. Third, as demand interactions scale up, both the market concentration and consumers' share of the surplus rise under broad conditions, so market-share based indices of concentration tend to suggest losses for consumers when the opposite is the case. We construct a generalized Herfindahl index which overcomes this limitation. Chapter III: Dominant Firms --- Many consumer industries evolve into partial oligopolies where firms with and without market power coexist. I develop a framework of dynamic competition which explains this pattern. Starting from a market with a continuum of firms, companies stochastically adjust their product offerings through the accumulation of thin-tailed innovations. In conjunction with discrete-choice founded demand, disruption becomes possible: if the spread of tastes relative to innovations' volatility falls below a threshold, occasionally a firm separates from the continuum with an outstanding product. As a result, this dominant firm accrues a positive market share and profit margin until a future innovator supplants it. During these cycles of disruptive turnover, the fringe provides a `seedbed': since incumbents emerge as frontrunners of the ongoing race of innovations, their products' qualities increase in the number of candidate firms from which they are drawn. Through this mechanism, the fringe’s measure is a first-order generator of surplus over time even if its output is not.
Open Access
Essays in modern Macroeconomics
Haber, Timo
This thesis contains three chapters, each addressing a highly relevant area of interest in modern macroeconomics. The first chapter tests the presence of state-dependent pricing frictions by analysing the effects of monetary policy during high inflation and after large monetary shocks. The second chapter focuses on the interaction of heterogeneity in firm potential with financial frictions and its effect on macroeconomic outcomes. The final chapter presents a global solution method for heterogeneous agent models that can handle interesting and relevent extensions to the standard setting.
Open Access
Essays in Macroeconomics
Ochs, Adrian
This thesis contributes to the study of identification in macroeconomics. The first two chapters combine machine learning techniques with econometrics to provide new insights into this long-standing question. I use natural language processing techniques in the first chapter to derive a novel monetary policy shock series. Interested researchers can readily extend this idea to other areas where large amounts of technical documents are available, for example, tax policies or financial markets. In the second chapter, we develop a new method to estimate state dependent policy effects. While researchers previously had to decide on the variables that determine the state, their interactions and their functional form, our approach nests these decisions in a data-driven way. We hope that our methodology simplifies the estimation of state dependent policy effects and leads to new findings in this area. The final chapter provides a novel approach to identifying expectation shocks in a fiscal policy VAR and discusses the particular case of constructing counterfactual impulse response functions for expectations. Both can be useful for studying other policy transmission mechanisms. The first chapter uses text analysis methods from the linguistic machine learning literature to construct a new monetary policy shock series. Measures of monetary shocks commonly give rise to the puzzling result that a monetary tightening has an expansionary effect. A possible reason is that agents may believe that monetary shocks contain infor- mation regarding the central bank’s assessment of the economic environment. Under this hypothesis, the estimated response to monetary policy shocks would contain two conflating effects: the actual effect of monetary policy and the reaction of private agents to the newly acquired information. This paper overcomes this problem by extracting a novel series of monetary shocks using text analysis methods on central bank documents. The resulting text-based variables contain the informational content from changes in the policy rate. Thus, they can be used to extract exogenous changes in monetary policy that are orthogonal to any central bank information. Using this information-free measure of monetary policy shocks reveals that a monetary tightening is not expansionary, even when estimated on more recent periods. The second chapter is co-authored with Christian Rörig and proposes a flexible frame- work to identify state dependent effects of macroeconomic policies. In the literature, it is common to either estimate constant policy effects or introduce state dependency in a parametric fashion. The latter, however, demands prior assumptions about the func- tional form. Our new method allows identifying state dependent effects and possible interactions in a data-driven way. Specifically, we estimate heterogeneous policy effects using semi-parametric varying-coefficient models in an otherwise standard VAR structure. While keeping a parametric reduced form for interpretability and efficiency, we estimate the coefficients as functions of modifying macroeconomic variables, using random forests as the underlying non-parametric estimator. Simulation studies show that this method correctly identifies multiple states even for relatively small sample sizes. To further val- idate our method, we apply the semi-parametric framework to a historical data set by Ramey & Zubairy and offer a more granular perspective on the dependence of the fiscal policy efficacy on unemployment and interest rates. Allowing for interactions between un- employment and interest rates, we show that it is indeed unemployment that is important to explain state dependent fiscal policy effects. The final chapter is co-authored with my supervisor Pontus Rendahl. In our paper, we empirically study the role of expectations in the transmission of fiscal policy. We extend an otherwise standard fiscal policy VAR with inflation and output expectations to construct counterfactual IRFs. Counterfactual IRFs allow us to ask how the economy would have responded to a government spending shock holding inflation or output expectations fixed. This exercise reveals that output expectations are the key driver in the transmission of government spending shocks. Output expectations contribute 60%-90% to the effect of government spending shocks on the fiscal multiplier at different impulse response horizons. We also make several methodological contributions. Firstly, we provide a novel way to identify shocks to expectations using lagged expectations as internal instruments. Secondly, we illustrate how to combine external and internal instruments to estimate a VAR’s impact effects with a single reduced form. Finally, we show that constructing counterfactual IRFs with a hypothetical shock series or setting zeros in the structural matrices of a VAR is equivalent.
Open Access
The Early Novels of Konstantin Fedin
(Faculty of Economics, 1969) Armes, Keith
An attempt has been made in this study to examine in depth the early novels of Konstantin Fedin. The novels discussed are Goroda i gody, Brat'ja, Poxiscenie Evropy, and Sanatorij Arktur, so that the period covered is from 1924 to 1940. Attention was paid primarily to Fedin's artistic method in an endeavour to establish the narrative techniques and literary devices characteristic of the author's work. The problem of characterization is also discussed in detail and the personalities of the principal figures are analyzed in the case of each novel. The question of chronology in Fedin's work has attracted considerable interest, and an analysis of the construction of the novels is provided with a view to establishing the time relationships within each novel. in addition, this study attempts to determine the actual period presented in each case, and it is claimed that new conclusions have been reached in this respect.
Open Access
Essays on Social Networks
To, Yu Yang Tony
This thesis consists of three essays on the economics of social networks. It broadly deals with understanding the value of social connections on favour exchange and information exchange. Social networks facilitate trust, learning, and communication, all crucial in the modern online environment. Examining the effects of network structure provides new tools and insights on decision-making and behaviour. Chapter 1 develops a model of repeated favour exchange on social networks where individuals choose between allocating the opportunity to the expert (market action) or a friend (favouritism action). Assuming favouring a friend reduces one’s payoff, favouritism cannot be sustained in a stage game. However, by introducing a grim-trigger strategy where a selective group of individuals favour each other, favouritism can be sustained in an infinitely repeated game. In particular, the maximum clique of the network defines favouritism behaviour that is coalition-proof where no group of individuals have incentives to deviate collectively. While aggregate surplus increases with network connectivity, it decreases with the number of favouritism-practising agents. Additionally, favouritism exacerbates payoff inequality that arises from degree inequality: Favouritism players cooperate to extract a large portion of the aggregate surplus at the expense of market players, creating a negative externality on the economy. Chapter 2 conducts an experiment to study the impact of network structure on opinion formation. At the start, subjects observe a private signal and then make a guess. In subsequent periods, subjects observe their neighbours’ guesses before guessing again. Inspired by empirical research, we consider three canonical networks: Erdös-Rényi, Stochastic Block and Royal Family. We find that a society with ‘influencers’ is more likely to arrive at an incorrect consensus and that one with ‘network homophily’ is more likely to persist with diverse beliefs. These aggregate patterns are consistent with individuals following a DeGroot updating rule. Chapter 3 studies incentives for verifying information in social networks. Agents derive value from sharing correct information and suffer a reputational loss from sharing false information. So agents can undertake costly verification prior to sharing information. We show incentives for verification are increasing in degree. This implies that information quality is increasing in average degree and is higher in more egalitarian networks. We then introduce an external agent whose goal is to maximise views through a choice of news source accuracy. We find that denser networks lead to higher accuracy when information accuracy is either expensive or cheap, and sparse networks lead to more accurate information otherwise.
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Essays on Medium-Term Economic Cycles and Real-Financial Linkages
Chen, Xiaohua
My PhD research studies medium-term economic cycles and real-financial linkages over the medium term under the supervision of Professor Solomos Solomou. The first paper (‘National and International Medium-term Economic Fluctuations since c.1870’) uses wavelet analysis to examine the time-profile of medium-term fluctuations using GDP and GDP per capita for 30 developed and developing countries since c.1870. The second paper (‘Endogenous Growth and the Financial Accelerator over Medium-term Business Cycles’) studies the mechanism of medium-term cycles in real economy and financial sector, with the structure model. The third paper (‘The Effects of Systemic Banking Crises’) is written with Dr. Bruno Rocha (University of Lisbon) and my supervisor Professor Solomos Solomou (University of Cambridge). We examine the medium-term effects of systemic banking crises on macroeconomy using a data set for a panel of 161 countries for the period 1970-2020, using the linear and non-linear local projection methods to estimate the impulse-response function. The last paper is a joint project with Dr. Nelson Sobrinho (International Monetary Fund). We produce an IMF working paper (‘A Framework for Assessing Low-Income Countries’ Capacity to Repay the IMF’). It is empirical research on the topics of real-financial linkages. Preserving low-income countries (LICs)’ ability to service their debt obligations including to the IMF is key for their continued access to concessional financing and development.
Open Access
Essays in Macroeconomics and Climate Change Mitigation
Hasna, Zeina
As carbon emissions reach unprecedented levels and threats of climate change mount, countries all over the world are racing to implement climate change mitigation policies to limit their carbon footprint and minimize climate risk. This dissertation explores the macroeconomic effects of climate change mitigation policies, namely carbon taxes and green energy investments. The first chapter, co-authored with Tiago Cavalcanti and Cezar Santos, evaluates the aggregate and distributional effects of climate change mitigation policies using a multi-sector equilibrium model with intersectoral input–output linkages and worker heterogeneity calibrated to different countries. The introduction of carbon taxes leads to changes in relative prices and inputs reallocation, including labor. For the United States, reaching its original Paris Agreement pledge would imply at most a 0.6% drop in output. This impact is distributed asymmetrically across sectors and individuals. In the US, workers with a comparative advantage in dirty energy sectors who do not reallocate suffer a welfare loss 12 times higher than workers in non-dirty sectors, but constitute less than 1% of the labor force. The second chapter estimates the local multiplier of spending in green energy in the United States. I construct a novel state-level dataset, and isolate the exogenous variation in green energy spending by exploiting the institutional characteristics of the green budget allocation by the Department of Energy (DoE). I find that a \$1 increase in green investment increases state-level output by \$1.1 contemporaneously, and up to $4.2 within two years of implementation. These estimates are large in comparison to the findings of the literature on public infrastructure multiplier, or the multiplier of non-green investments by DoE. The third chapter builds on the second chapter and provides an empirical and a theoretical breakdown of the local green multiplier in the United States to understand why it is large. Empirically, I find that green energy spending has significant effects on state sectoral output, state-level employment, and state-level investment. Quantitatively, I contrast green and nongreen multipliers by specifying an open economy New Keynesian model with public capital, where each US state is an open economy within a fiscal and monetary union. I calibrate the public capital to green and non-green energy using a transaction-level dataset on awards by the Department of Energy. Model-based counterfactual experiments suggest that 86% of the difference between the green and non-green multipliers is explained by the initial stock of public capital in each energy type. As green public capital is further away from the steady-state, the marginal productivity of investment is higher in the short-run, leading to higher multipliers relative to investment in non-green public capital.
Open Access
Essays in Macroeconomics and Firm Dynamics
Vaziri, Maryam
This thesis contains three chapters and employs empirical and structural tools to study determinants of productivity growth and resource misallocation among firms in the economy. The first chapter studies the implications of financing constraints on optimal expansion strategies of multiple-product firms and their consequent effect on aggregate productivity level. In particular, this chapter seeks to understand how firms may prioritise expanding their domestic product scope over exporting when they have limited access to financing. To answer this question, I develop a firm dynamics model in which firms are heterogeneous in terms of their productivity and access to financing. Analytically, I find that a firm with sufficiently high levels of productivity but low access to financing overcomes its financing constraints by expanding in the domestic market with lower productivity goods and then exporting. I verify this result by structurally estimating an international trade model that matches the moments of the US economy in the early 2000s. I estimate that removing financing constraints would increase the aggregate productivity level by 3.1%. The second chapter provides an empirical investigation of the relationship between the enforcement of antitrust law and various macroeconomic outcomes such as productivity growth, firm entry rate, and investment in Research and Development for two cases: the US and Europe. For the US, I proxy antitrust enforcement by the relative share of antitrust budget, and combine it with firm-level and sector-level data. Similarly, for Europe, I use firm-level and sector-level data together with an antitrust index capturing variation of law across countries and over time. Through both exercises, I find that in more concentrated industries stronger antitrust policies are associated with higher productivity growth, higher entry rate but lower investment in Research and Development. This chapter serves as a motivation to the results in chapter 3. The third chapter develops a structural model to study firms’ strategic and anticompetitive actions, and the consequent role of antitrust law as a macroeconomic policy in generating higher productivity growth. In this chapter, I propose a dynamic general equilibrium model with innovation and oligopolistic product market competition. The oligopolistic competition provides firms with market power, which combined with a dynamic setup, implies that firms may find it optimal to eliminate their competitors through strategic decision making. I then structurally estimate the model to match the recent US experience. Through a quantitative exercise, I find that strengthening antitrust policies improves business dynamism on various fronts: (1) firm entry rate increases, (2) productivity growth improves, (3) labour share of GDP becomes higher, (4) while innovation proxied by the relative share of R&D expenditure falls. The model shows that stronger antitrust policies can improve welfare by up to 16% in consumption equivalent terms.
Open Access
Exchange Rates, Capital Controls and the Hegemon's Dilemma
Marin, Emile
In this thesis, I study the interplay between exchange rate dynamics and capital flows in the international macroeconomy, and I consider the optimal policy response for economies that are large in goods and financial markets. I focus on features characterising the modern International Monetary System: the predictability and excess volatility of exchange rates, large and volatile capital and trade flows, and the search for safe (particularly dollar) assets by foreign investors. Chapter 1 provides a brief introduction of the topics studied and methodologies used, high- lighting why the questions I tackle are relevant. Chapter 2, which is co-authored with Simon Lloyd and is entitled Exchange Rate Risk and Business Cycles, presents an empirical study of exchange rate dynamics and, using a simple asset-pricing framework, it links them to business cycle risk and cross-country liquidity yields. We show that currencies with a steeper yield curve depreciate at business-cycle horizons. We identify a tent-shaped relationship between exchange- rate risk premia (ERRP) and the relative yield curve slope across horizons that peaks at 3-5 years and is robust to a number of controls, including liquidity yields. Within the asset-pricing framework, ERRP reflect investors’ changing return valuations over the business cycle. We then calibrate a two-country, two- factor model of interest rates, where exchange rates are driven by business-cycle —transitory and cyclical—risk. The model quantitatively reproduces the tent- shaped relationship, as well as variation in uncovered interest parity coefficients across horizons. In chapter 3 entitled Capital Controls and Free Trade Agreements, also co-authored with Simon Lloyd, we study the joint optimal determination of trade tariffs and capital controls in a two- country, two-good model with trade in both goods and assets. Policy is driven by the incentive to manipulate the terms of trade both across goods and over time. When tariffs are ruled out by a free-trade agreement (FTA), capital controls are chosen to trade-off the two margins. Absent a FTA, the planner achieves weakly higher welfare by additionally employing tariffs on goods. However, time-varying tariffs have second-best effects on the cost of borrowing, so the size of optimal capital controls depends on trade policy. Specifically, in response to fluctuations in the endowment of goods consumed with home bias, capital controls are larger when the optimal tariff is in place. In contrast, faced with fluctuations in the endowment of the second good, the optimal time-varying tariff partly substitutes for the use of capital controls, so capital controls are smaller. Our results extend to a Nash equilibrium where countries engage in both capital-control and trade wars. Chapter 4, entitled The Hegemon’s Dilemma, is single-authored. I show that by keeping dollars scarce in international markets, the U.S. –the hegemon– earns monopoly rents when borrowing in dollar debt and investing in foreign-currency assets. However, in equilibrium, these rents result in a strong dollar, which depresses global demand for its exports and leads to losses on existing holdings of foreign assets, and give rise to private sector over-borrowing. Using an open economy model with nominal rigidities and segmented financial markets, I show that, because of over-borrowing, monetary policy alone cannot achieve the constrained efficient allocation. Absent a corrective macro-prudential tax on capital inflows, the hegemon faces inefficiently volatile output and prices, and lower monopoly rents. By increasing liquidity in international markets, dollar swap lines extended by the central bank improve stabilisation, but, unlike macro-prudential taxes, do so at the cost of eroding monopoly rents for the hegemon. In contrast, dollar swaps improve outcomes for foreign investors. Dollar shortages can also have distributional consequences for the hegemon. A scarce dollar leads to larger monopoly rents which benefit financially-active households, but they over-borrow at the expense of inactive households, who suffer the full brunt of aggregate demand externalities.
Open Access
Essays in Macroeconomics and Heterogeneity
Rörig, Christian
This thesis contains four chapters, addressing two separate but equally prominent research areas in macroeconomics. The first two chapters focus on the effects of firm heterogeneity and firm dynamics on macroeconomic outcomes, particularly how the transmission of macroeconomic shocks is impacted by strategic behaviour and the distribution of financially constrained firms. The last two chapters address the topic of identification in macroeconomics with the last chapter focusing on the measurement of heterogeneous dynamic effects after a macroeconomic policy shock. The first chapter examines how oligopolistic competition, firm heterogeneity and entry of firms alter the transmission of monetary policy through the lens of a New Keynesian model. The standard textbook New Keynesian model relies on counter-cyclical profits for monetary policy to have an effect as recently pointed out by Broer et al. (2020). This paper first tests this hypothesis by adding oligopolistic competition and static free entry to an otherwise standard NK model. Including search and matching frictions to the labour market, breaks the result of money neutrality despite free entry of firms. Beyond that the model is further augmented to accommodate firm heterogeneity and dynamic entry to investigate how the market structure affects the propagation of monetary policy shocks. The findings are threefold: First, through the channel of oligopolistic competition, heterogeneity in firms’ productivity leads to pro-cyclical profits for lower levels of wage rigidity compared to the homogeneous case. Second, firm heterogeneity increases the response in aggregate output which is in line with Mongey (2017). Third, dynamic entry is further enhancing this effect, yet the strengthening of competition has a negative impact on firms’ profits. Local projections using Compustat firm-level data and Romer & Romer (2004) monetary policy shocks support the predictions of the theoretical model. The second chapter, which is co-authored with Miguel H. Ferreira and Timo Haber, investigates how distributional properties of financially constrained firms shape macroeconomic outcomes. Using a unique dataset covering the universe of Portuguese firms and their credit situation we revisit the relation between firm size, their financial situation, and sensitivity to the cycle. First, we provide two stylized facts: (1) Financially constrained firms react more to the business cycle and this mechanism is orthogonal to the size channel proposed by Crouzet & Mehrotra (2020). (2) Constrained firms are found across the entire size distribution, also in the top percentiles, which is in contrast to what standard financial friction models would predict. We then show that ex-ante heterogeneity of firms, a possible explanatory factor, persists over the firms’ life cycle and affects constrained and unconstrained firms differently. Incorporating this ex-ante heterogeneity into an otherwise standard financial frictions model simultaneously accounts for the stylized facts, gives rise to large constrained firms, and leads to larger aggregate fluctuations and capital misallocation. In the third chapter, together with my supervisor Pontus Rendahl, we investigate the effect of saving shocks on business cycle fluctuations. A common modeling tool – and a popular narrative – used to explain the financial crisis of 2008-2010 is a sudden increase in the desire to save. Such “marginal propensity to save” (MPS) shocks can be triggered by, for instance, a rise in uncertainty surrounding the economic climate, and depress interest rates, inflation, and generally cause an economic contraction. This paper uses the long-run properties arising from MPS shocks in both exogenous- and endogenous growth models with sticky prices in order to identify their causal effect on output. We find that time series data from the United States is strongly supportive of the notion that MPS shocks indeed have a causal, and contractionary, effect on economic activity, lending support to the most common approach of studying the financial crisis. The fourth chapter is co-authored with Adrian Ochs and aims to improve and facilitate the measurement of heterogeneous macroeconomic policy effects by using machine learning techniques. Specifically, the paper proposes a flexible framework to identify state-dependent effects of macroeconomic policies. In the literature it is common to either estimate constant policy effects or introduce state-dependency in a parametric fashion. This, however, demands prior assumptions about the functional form. Our new method allows to identify state-dependent effects and possible interactions in a datadriven way. Specifically, we estimate heterogeneous policy effects using semi-parametric varying-coefficient models in an otherwise standard VAR structure. While keeping a parametric reduced form for interpretability and efficiency, we estimate the coefficients as functions of modifying macroeconomic variables, using random forests as the underlying non-parametric estimator. Simulation studies show that this method correctly identifies multiple states even for relatively small sample sizes. To further illustrate our method, we apply the semi-parametric framework to the historical data set by Ramey & Zubairy (2018) and offer a more granular perspective on the dependence of the fiscal policy efficacy on unemployment and interest rates.
Open Access
Time Series Models for Finance and the Environment
Palumbo, Dario
This thesis is focused on presenting novel filtering methodologies for modelling and analysing features of financial and environmental time series. The methodology used in the chapters is based on the novel observation-driven dynamic conditional score (DCS) class of time series models. The first chapter sets up a DCS model based on the Generalised Beta of the second kind conditional distribution for modelling realized volatility (RV). Given its general formulation, it is capable of effectively capturing the long memory of the RV process with two first-order components, together with a day of the week effect both levels and in logarithms. It is also able to model and detect heteroscedasticity in log RV, which may be interpreted as the dynamic tail index in levels. Its forecasting performance is compared with that of fractional integrated models and the popular heterogeneous autoregressive model. The second chapter examines the occurrence of extreme observations over time. It introduces a dynamic DCS model for the shape parameter that governs the tail index based on the Generalised t family of conditional distributions. The model also allows for asymmetry with different dynamics for the left and right tail index parameters. In addition the chapter introduces and studies the size and power properties of a new Lagrange multiplier test to detect the presence of dynamics in the tail index parameter. The third chapter provides a novel methodology based on a cylindrical distribution for the joint modelling of circular and linear variables such as wind direction and velocity. The model is capable of exploiting additional information from the data to provide a new simple solution to model both data series even in absence of wind. The chapter provides an extension which allows to test and model the variations over time of the concentration parameter, which can be interpreted as time varying volatility of wind direction. The framework is further extended to allow for the possibility of modelling multiple regimes in wind direction giving dynamics directly to the switching probabilities. This approach is shown to provide significantly superior fit in comparison with the standard hidden Markov model framework used in the literature.
Open Access
Model Selection, Uniform Inference and Nonparametric Regression
De Boeck, Alexis
Model selection in the nonparametric regression model is inevitable since any nonparametric estimator requires tuning parameters to be specified in order for it to be feasible. It is, however, standard practice to carry over the theory of nonparametric estimators when the model is fixed to the case where the tuning parameters are no longer fixed, but chosen by, possibly, data-driven model selection algorithms. This theory is not necessar ily valid as the model selection step is not taken into account. This thesis contributes to the nonparametric econometrics and statistics literature and, in particular, to the theory of series estimators, by showing that such estimators have desirable properties and that valid inference is possible even when a model-selection step precedes estimation. The first chapter is concerned with K-fold cross-validation and shows that the cross- validated least-squares estimator predicts the response equally well as the unfeasible best-linear predictor whose dimension may diverge with the sample size. This property, known as risk consistency, is uncommon in econometrics, but it has the benefit that it holds under few and very weak conditions. The risk-consistency result crucially re lies on the non-asymptotic analysis of the difference between the prediction error of the cross-validated estimator and the best-linear predictor. As the dimension of the parameters may diverge, this set-up analyses both the high-dimensional linear model as well as the nonparametric regression model which reduces the need for duplicate theories. An extensive Monte Carlo experiment corroborates the theoretical results by showing that the non-asymptotic bound becomes arbitrarily small as the sample size diverges. The second chapter returns to more classical statistics and econometrics by studying the uniform consistency of the series estimator for the conditional mean function and its linear functionals. The uniformity holds both in the support of the covariates as well as the models considered. Under high-level assumptions, a non-asymptotic linearisation result delivers uniform rates of convergence for the series estimator. By verifying the high-level assumptions, case-specific rates can easily be derived. For example, the series estimator attains, up to a small logarithmic penalty, the minimax rate of convergence for functions lying in a Hölder ball. The results from the second chapter form the basis for the inference procedure proposed in the final chapter in order to construct valid uniform confidence bands for the series estimator. The uniform confidence bands are valid in the sense that they control the asymptotic size for the conditional mean function, or its linear functionals, seen as a process in the covariates and the models considered. Given that the results hold uniformly over the models considered, the inference procedure is valid regardless of which model-selection algorithm delivers the final model used to estimate the parameters of interest. The key quantity is the maximal t-statistic correctly studentised using an estimator for the standard error. The theory relies on the uniform linearisation result from chapter two and the concept of strong approximations, or couplings, as the limit distribution of the maximal t-statistic does not exist. A Monte Carlo study establishes that the uniform confidence bands have the correct coverage even in finite samples. The chapter concludes with an application testing for shape restrictions on the demand function for gasoline in the US using a cross-validated series estimator.
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Essays on Information in Financial Markets
Hennig, Tristan
Chapter 1 demonstrates how to jointly quantify the size of search and information frictions in OTC markets. I use transaction data for the U.S. corporate bond market to structurally estimate a model featuring both frictions via the simulated method of moments. The data support the notion that trades are informative and that uncertainty about the fundamental value diminishes as time passes. The model allows me to evaluate the rise of electronic trading as well as recent regulation such as MiFID II, both of which have reduced the severity of the search friction in OTC markets. Increasing the probability of finding a trading partner by 20% decreases spreads by 18 percent on average, increases welfare by 21.8 percent on average, and decreases price volatility by 40 percent on average. The effects are biggest in bonds with long time to maturity and smallest in bonds close to maturity. However, these improvements come at the cost of a substantial slow-down in price discovery. The speed of convergence of the price to the true value decreases by up to 26 percent. Chapter 2 is joint work with my supervisor. We present a sequential trade model in the tradition of Glosten and Milgrom (1985). In our model, agents receive informative but imperfect information about the fundamental value of a security and learn by observing others’ trading decisions. Herding occurs when traders ignore their private information to switch in the direction of the crowd. Similarly, contrarianism occurs when traders ignore their private information to switch against the crowd. Using NYSE TAQ tick data, we estimate our model by maximum likelihood and show that it fits the data significantly better than existing models by Easley et al. (1997) and Cipriani and Guarino (2014). The event uncertainty setup commonly used in this literature is rejected in favour of a general three-state setup. We find that contrarianism occurs very rarely and has negligible price impact. In contrast, about 35% of days in our sample feature herd behaviour at some point during the day. Compared to existing results, we show that herding is more frequent, has a more variable duration, occurs later in the day, and causes higher deviations of the price from an informationally efficient benchmark. The data also support the notion that herd behaviour is self-reinforcing rather than self-destructive. Chapter 3 is divided into two self-contained but related parts. The first part addresses a key assumption made in sequential trade models, namely that changes in the security's fundamental value only occur in between trading days. I show that this assumption can easily be relaxed and present two results. First, the data do not support the assumption that fundamental value changes only occur over night but instead are much more frequent. Second, when the model is adjusted to allow for within-day value changes, the extent of herd behaviour that is predicted by the model is substantially reduced. The second part of this chapter develops a model that departs from another assumption typically used in sequential trade models. Instead of restricting agents to either buy or sell a single unit of the security, I allow the action space to be the real line. Despite the unrestricted continuous action space herding and contrarianism can still arise in equilibrium. Using transactions data I show how to estimate the model via maximum likelihood. The results demonstrate that using only the trade direction instead of all information contained in the volume data can bias the results. Chapter 4 studies the nature of trading when market participants are not perfectly rational Bayesians. The standard way of modelling decision making under uncertainty assumes that agents update their beliefs about uncertain variables in a statistically correct way. In this chapter, I introduce a notion of bounded rationality that constrains agents to entertain only a finite number, rather than a continuum, of posterior beliefs. Given this constraint, I analyse how coarse beliefs can be structured optimally. I then introduce a mass of traders with coarse beliefs into a simple financial market and explore the effects on the price of an asset with an uncertain payout and on trading between the agents. Introducing agents with coarse beliefs into an asset market generates trading that would otherwise not occur.
Open Access
Essays on Probabilistic Machine Learning for Economics
Kuhlen, Nikolas
This thesis consists of three essays that explore the use of probabilistic machine learning techniques in combination with information-theoretic concepts to answer economic questions. Over the past years, economists have started applying machine learning methods to a wide range of topics. Probabilistic methods in the context of unsupervised learning represent one particular modelling approach at the intersection of computer science and statistics. While widely used in applied statistics, these models, however, do not necessarily provide relevant and interpretable outputs from an economist's perspective. In this thesis, I appeal to information-theoretic methods to summarise the probabilistic information inferred from such models and construct economically meaningful measures.
Open Access
Bargaining Theory
(1988-01-29) Muthoo, Abhinay
This thesis is devoted to the study of bargaining using the methods of non-cooperative game theory. In Part I (chapters 1 and 2) we examine the role of commitment in bilateral bargaining. Two different notions of commitment in bargaining are explored in two different non-cooperative infinite-time horizon sequential games with complete and perfect information. In Part II (chapters 3 and 4) we examine the role of outside options in bilateral bargaining. Two models are presented, each model is a non cooperative infinite-time horizon sequential game with complete information. The two models differ in their approach to modelling the interlacing of the search and bargaining processes. In the final part of this thesis, Part III (chapter 5)z we present a a of decentralised market, based on the idea that the agents of the market search for partners with whom to trade and when a buyer and a seller meet they initiate a sequential bargaining process over the terms of trade.
Open Access
Inequality in Political Representation
Lee, Su-Min
In many countries the near-universal right to vote in elections has been a core attribute of their democratic institutions for decades, and in some cases over a century. However, the political experience of many of these very countries over the past decade have often alternated between apathy and frustration in these democratic institutions. Stark economic inequalities have mirrored inequalities in political influence, voters observing that elected officials who determine policy are disproportionately from a political elite or establishment. Why, after decades of near-universal voting rights, are only five percent of MPs in the UK House of Commons from the working class, and only one in four legislators in the United States are women?
Open Access
Essays in Macroeconomics and Asset Pricing
Lu, Jason
The dissertation presents three essays on asset pricing in the context of Macroeconomics. Each chapter develops upon a central theme: that asset price bubbles act to drive fluctuations in the aggregate economy and conversely are themselves a symptom of economic conditions. The dissertation presents arguments and evidence in support of this theme. The implication is that these types of asset price fluctuations are important to study if we wish to develop a full understanding of the macroeconomy as a larger integrated system. In my first chapter, I study the effects of bubbles on a secular stagnation economy. In such a setting, a negative natural rate of interest drives a deficit of demand and a persistent output gap. I find that bubbles act to increase the natural rate of interest, hence they alleviate the cause of secular stagnation. This suggests a positive role for bubbles, however bubbles are intrinsically unstable. Larger bubbles are shown to be more unstable, and upon collapse the natural rate of interest falls, potentially triggering secular stagnation. In the second chapter, I offer a demographic explanation to the secular decline in interest rates. Fertility rates fell dramatically in the early 1970s, which created a distortion in the age distribution with the cohort born just before the fertility fall being disproportionately larger than the cohorts born both before and after. As this large cohort accumulates assets for retirement, their savings flood the capital market leading to a collapse in interest rates. The model offers an explanation for the fall in interest rates over the last three decades. Furthermore, it predicts that real interest rates will continue to fall until hitting a trough around the year 2035. Despite the fall in interest rates, the model does not provide a rationale for the rise in land prices. This chapter is a co-authored work with Coen Teulings. In the final chapter, I develop a model for house price dynamics driven by short and long-term shocks to housing fundamentals. I consider households who have incomplete information and cannot directly observe underlying changes in fundamentals. Instead, they solve a Bayesian signal extraction problem to infer fundamentals from prices. In contrast to the complete information benchmark, my model replicates the observed empirical short-term momentum and long-term reversal in prices, which are often associated with speculation in housing markets. Furthermore, I show that a sequence of positive short term shocks generates an expectations-driven boom and bust in housing that is of far greater magnitude than in the complete information benchmark. Finally, I demonstrate an application of my model to identify episodes of bubbles in US house price data.
Open Access
Essays on Labour Supply, Retirement, and Consumption
(2021-09-18) Oh, Taehee
This PhD dissertation is a study of the individual level behaviour of labour supply, retirement, and consumption in different contexts. The first chapter studies the importance of intrafamily supports in elderly people's work and retirement choice. I build a dynamic programming model with extended families consisted of elderly parents and their adult-child households who do not live together, are imperfectly-altruistic toward each other and engage in a non-cooperative dynamic game. The two key innovations are allowing both parents- and child-household to provide transfers to each other and investigation of joint decisions making in older people's labour supply, savings, and intrafamily transfer choices. The structural parameters are estimated using the Korean Labour and Income Panel Study. I find that taking account of inter-vivos financial transfers can provide a better explanation of older people's life-cycle choices and reliance on government supports. The estimated model is used to evaluate the impact of two policies of social security expansion on elderly people's life-cycle choices. First, the expansion of guaranteed minimum income for the elderly results in crowding-out private transfers and unintended redistribution of resources rather than mitigating old-age poverty. Also, the welfare evaluation of policy can be biased if the strategic interaction between family members is not accounted for adequately. Second, the rise in state pension income amount just has a limited effect on older people's work incentives, and the vast amount of intrafamily resource sharing could be partly caused by high elderly poverty. The second chapter builds and estimates a dynamic model of older people's joint decisions of labour supply, savings, and social security benefit (SSB) application. One new feature of the model relative to the existing literature is that I allow for the selection into self-employment jointly with paid-employment and retirement. Agents in the model observe their own paid-sector productivity but are uncertain of their productivity in the self-employment sector. However, the learning process enables people to reduce initial uncertainty by observing the performance of their business. The parameters of the dynamic programming model are estimated using the U.S. Health and Retirement Survey. I find that allowing for the transition between paid- and self-employment delays the retirement of older workers. In the counterfactual simulation, I compare the effects of payroll tax-cut and self-employment subsidy program and find that these policies can contribute to strengthening security in retirement and have a large effect on the proportion of people who choose paid- and self-employment. However, they have limited effects on elderly people's retirement choice. The third chapter is co-authored with Kai Liu, Shawn Ni and Youn Seol. We estimate the wealth effect on consumption by exploiting the differential effect of housing price booms and busts across households with different holdings in housing wealth. We also extend the analysis of the wealth effect from the consumption growth to its inequality by allowing income shocks and the ability to smooth consumption against income shocks to vary over housing wealth and housing market-driven wealth shocks. Using household-level panel data on consumption, income, and wealth from the Korean Family Income and Expenditure Survey, we find that the house price change has a significant and large differential effect on consumption growth, and homeowners exhibit a stronger ability to insure consumption against income fluctuations. Also, the ability to insure consumption against income risks is imperfect, and the effect of transitory shocks on consumption is smoothed more than that of permanent shocks.