Under 1990-talet infördes radikala, marknadsorienterade reformer i Sverige som gav upphov till utökade möjligheter att välja andra skolor än de kommunala. Syftet med denna uppsats är att undersöka huruvida föräldrar värderar att bo i ett område med fler skolalternativ. Vi gör detta genom att studera effekten av andelen friskoleelever i en kommun på bostadspriser i kommunen. Studien använder paneldata på kommunnivå från 2010 till 2018 hämtad från Statistiska Centralbyrån (SCB) och Skolverket. Det empiriska sambandet analyseras med fixed effects modeller vilket möjliggör kontroll för års- och kommunfixa effekter. Resultatet visar att det finns ett positivt men statistiskt icke-signifikant samband mellan andelen friskoleelever och huspriser. Resultatet är robust mot en rad utförda känslighetstester. Studien finner således inte belägg för att föräldrar söker sig till områden med fler skolalternativ. Detta ger vare sig stöd för fortsatt implementering av liknande reformer som främjar alternativ till den kommunala skolan eller reformer som reducerar möjligheterna till skolval. / During the 1990s radical, market oriented reforms were implemented in Sweden which allowed for increased opportunities to choose other schools than the public. The purpose of this thesis is to examine whether parents value living in an area with more school options. We do this by studying the effect of the share of pupils who are enrolled in a private school in a municipality on housing prices in that municipality. The study uses paneldata on the municipality level from 2010 to 2018 gathered from Statistics Sweden and the Swedish National Agency for Education. The empirical relationship is analyzed using fixed effects models which makes it possible to control for year and municipality fixed effects. The results show that a positive but statistically insignificant relationship exists between the share of private school students and housing prices. The result remains robust for different sensitivity tests. Therefore, the study does not find support for the assumption that parents value living in an area with more school options, which neither provides basis for further implementation of similar reforms that promote alternatives to public school nor reforms that reduce school choice.

How are the prices of financial assets determined? In this dissertation, I test various theories empirically, focusing on several classes of bonds. In the first chapter, I test whether asset prices reflect the risk-exposures of financial intermediaries in a setting that is well suited to tackling concerns about omitted risk factors. I analyze catastrophe bonds whose cash flows are linked to the occurrence of natural disasters and find that 71% of the variation in their expected returns can be explained by a theoretically-motivated measure of financial intermediaries’ marginal rate of substitution. Assuming that natural disasters are independent of aggregate wealth, this pricing result is inconsistent with any explanation based on macroeconomic risk factors. However, the result is consistent with intermediary asset pricing models that suggest that financial intermediaries are marginal investors in capital markets. I also show that the premium on natural disaster risk has decreased significantly in recent years and has become less responsive to the occurrence of disasters, suggesting that intermediaries’ access to outside capital has improved over time. In the second chapter, which is coauthored with Robert J. Hodrick, we examine the statistical term structure model of Cochrane and Piazzesi (2005) and its affine counterpart, developed in Cochrane and Piazzesi (2008), in several out-of-sample analyzes. The model’s one-factor forecasting structure across bonds with two, three, four, and five years to maturity characterizes the term structures of additional major currencies in samples ending in 2003. In post-2003 data such one-factor structures again characterize each currency’s term structure, but we reject equality of the coefficients across the two samples. We derive currency return forecasting implications from the Cochrane and Piazzesi (2008) affine model showing that the term structure forecasting variables in each currency should predict cross-currency investments, but we find no support for these predictions in either pre-2004 or post-2003 data, whereas the interest differentials do predict currency returns. Here too, though, we find strong evidence of parameter instability as the parameter estimates on the interest differentials change sign. In recursive out-of-sample forecasts of excess rates of return on bonds in each currency, the Cochrane and Piazzesi (2008) term structure forecasting models fail to beat forecasts from the historical average excess rates of return. Graphical analysis indicates that the instability in the forecasting models’ parameters begins in the global financial crisis.

Den här studien utvärderar potentialen i söktermsdata från Google som ledande indikator för priser på bostadsmarknaden i Stockholm. Det prediktiva innehållet i söktermsdata från Google Trends jämförs mot en mer klassisk prognosmodell byggd på makroekonomiska variabler. Genom att mäta avvikelsen i en pseudo-prognos redovisas respektive datakällas förmåga till riktiga prognoser. Den huvudsakliga slutsatsen är att det finns resultat som styrker tesen om prediktivt innehåll i Googledata, framförallt för prognoser med horisonter upp till sex månader. Genom att använda Googledata skapas prognoser som har en mindre avvikelse från den faktiska tidsserien är vad modellen byggd på makroekonomiska variabler kan leverera. Resultatet visar på användbarheten i söktermsdata från Google som ledande indikator för priser på bostadsmarknaden i Stockholm. / This study evaluates the potential in using Google search term data as a leading indicator of prices on the real estate market in Stockholm. The predictive content of the search term data from Google Trends is contrasted against a more classic forecasting model using macroeconomic variables. The ability of each data source to generate powerful forecasts is demonstrated by measuring the deviation in a pseudo-forecast. The main finding is that the results support the hypothesis on predictive content in Google data, mainly forecasts with up to six months’ horizon. By using Google data, forecasts can be made with less deviation from the actual time series than forecasts built on macroeconomic variables. The results point to the usability of search term data from Google as a leading indicator for prices on the real estate market in Stockholm.

Den 11 mars 2020 klassades Coronaviruset som en pandemi och har sedan dess kommit att påverka såväl den svenska ekonomin som arbetslöshet och bostadsmarknad. Till följd av Coronapandemin sköts allt fler jobb på distans och efterfrågan på större bostäder har ökat. Likaså har efterfrågan på utbildning växt och antalet studerande ökat. Den lågkonjunktur som förväntades drabba ekonomin har lett till beslut om slopat amorteringskrav och att behålla reporäntan på noll procent. I uppsatsen analyseras data från Svensk Mäklarstatistik, som inkluderar bostadsrätter sålda under perioden 1 mars 2019 till 31 december 2020, samt kompletterande data från Booli för perioden 1 januari 2019 till 28 februari 2019. I syfte att fokusera på unga förstagångsköpare som riskerar att bli utkonkurrerade när efterfrågan på bostäder ökar, inkluderas endast bostadsrätter mindre än 50 kvadratmeter i studien. Genom metoden difference-in-difference analyseras prisförändring på bostadsmarknaden i Uppsala kommun perioden före och efter att Covid-19 etablerat sig. Som jämförelsegrupp används bostadsrätter sålda under samma period ett år tidigare. De huvudsakliga resultaten visar att effekten av Covid-19 på priserna för bostadsrätter under 50 kvadratmeter var positiv. Statistiskt signifikanta resultat fås när kontrollvariabler för BNP och ränta inkluderas. / March 11th, 2020, the Coronavirus was classified as a pandemic and has since come to affect the Swedish economy, unemployment and the housing market. As a result of the Covid-19 pandemic, more jobs are being managed remotely and the demand for larger homes has increased. Similarly, the demand for education has grown and the number of students has increased. The recession, which was expected to hit the economy, led to a decision to abolish amortization requirements and to maintain the repo rate at zero percent. The thesis uses data from Svensk Mäklarstatistik, which includes condominiums sold between the period March 1st 2019 to December 31st 2020, as well as supplementary data from Booli.se for the period January 1st 2019 to February 28th 2019. Only condominiums under 50 square meters are included, in order to focus on first-time buyers who risk being outcompeted when the demand for condominiums increases. Through a difference-in-difference study, the aim is to analyze price changes in the housing market in Uppsala municipality, analyzing the period before and after Covid-19 established. As a comparison group, condominiums sold during the same period one year earlier are used. The main results show that final prices for condominiums under 50 square meters increased. Statistically significant results are obtained when control variables for GDP and interest rates are included.

This dissertation studies topics in Passive Investing and Asset Pricing. The first chapter, "When do flows matter for asset prices: Evidence from adoption of ETF creation in Israel," focuses on the effect of capital allocation to passive investments on asset prices. We study a 2012 reform in Israel where all exchange traded products listed on the Tel Aviv Stock Exchange (TASE) adopted the Exchange Traded Fund (ETF) creation mechanism wherein designated market makers arbitrage between the index price and the net asset value of its benchmark. The reform greatly decreased the cost of this arbitrage activity and translated into a significant increase in demand for passive investments. The effect was stronger for illiquid indices containing smaller stocks. We show that the price effects of the reform were dramatically higher for stocks located at the top of indices composed of smaller stocks relative to stocks at the bottom of indices composed of bigger stocks. A 1 p.p. increase in passive ownership as a percent of market capitalization leads to an 11.7% increase in the price of stocks. Our findings provide new evidence on how passive inflows can change the distribution of capital across indices, and in turn impact price efficiency. In the second chapter, "Passive Investing and Algorithmic Trading," I examine the trading behavior of market participants against the growing demand for passive investing. I show that the growth of passive investing and algorithmic trading is complementary and mutually reinforcing. Algorithmic traders respond to a spike in demand for passive investments listed on the TASE following a major reform in the Israeli index market in 2012 by front-running the index inflows. Algorithmic traders accumulate stocks when index inflows are low and sell stocks when they are high. Based on this strategy, algorithmic traders earn a 12.7% annualized return in realized gains over passive strategies in the same period. Instead, Mutual Funds load on the index when inflows are high.

With increased availability of data in various fields, researchers often need to combine efficient empirical methods with innovative analytical modeling techniques to make data-driven decisions and gain managerial insights from the large-scale raw data. In light of this, my thesis combines empirical methods and analytical modeling to study several data-related problems in the fields of financial economics and healthcare management. The first two parts of the thesis focus on two topics in financial economics: the role of dynamic information in asset pricing and the link between index-based investment and intraday stock dynamics. The last two parts of the thesis study the ICU admission decisions and cardiac surgery scheduling using data from different hospital units. The first part of the thesis focuses on the role of information in financial market. As a fundamental topic in asset pricing, information is known to play an important role in determining asset prices and market volatility. In most of the existing literature, the information environment, i.e., the amount of knowable information, is assumed to be fixed and independent of investor's choice. However, in a dynamic market, the level of available information can vary substantially due to changes in technology and regulations. On the other hand, rational news producers may respond to investors' demand for information. Such effects are commonly seen in the reality, but are less studied in the literature. To bridge this gap, we develop a model of investor information choices and asset prices where the availability of information about fundamentals is time-varying. A competitive research sector produces more information when more investors are willing to pay for that research. This feedback, from investor willingness to pay for information to more information production, generates two regimes in equilibrium, one having high prices and low volatility, the other the opposite. Information dynamics move the market between regimes, creating large price drops even with no change in fundamentals. In our calibration, the model suggests an important role for information dynamics in financial crises. In the second part of this thesis, we investigate how the growth of index-based investing impacts the intraday stock dynamics using a large high-frequency dataset, which consists of 1-second level trade data for all S&P 500 constituents from 2004 to 2018 (500GB). We estimate intraday trading volume, volatility, correlation, and beta using estimators that are statistically efficient under market microstructure noise and observation asynchronicity. We find the intraday patterns indeed change substantially over time. For example, in the recent decade, the trading volume and correlation significantly increase at the end of trading session; the betas of different stocks start dispersed in the morning, but generally move towards one during the day. Besides, the daily dispersion in trading volume is high at the market open and low near the market close. These intraday patterns demonstrate the implication of the growth of index-based strategies and the active-open, passive-close intraday trading profile. We theoretically support our interpretation via a market impact model with time-varying liquidity provision from both single-stock and index-fund investors. In the third part of the thesis, we study the intensive care units (ICUs) admission decisions in a large hospital system. In the case of ICUs, which provide the highest level of care for the most severe patients, it is known that admission rates of some patients decrease as occupancy increases. It is also known that, for at least some conditions, ICU admission is not just a function of patients’ illness, and that a significant proportion of the variation in ICU admission rates is due to hospital, not patient, factors. To understand such variation, we employ two years of data from patients admitted to 21 Kaiser Permanente Northern California ICUs from the ED. We quantify the variation in ICU admission from the ED under varying degrees of ICU and ED occupancy. We find that substantial heterogeneity in admission rates is present, and that it cannot be explained either by patient factors or occupancy levels alone. We use a structural model to understand the extent that intertemporal externalities could account for some of this variation. Using counterfactual simulations, we find that, if hospitals had more information regarding their behaviors, and if it were possible to alter hospital admission processes to incorporate such information, hospitals could reduce their ICU congestion in a safe way. The last part of the thesis focuses on the impact of system workload on service time and quality in the context of cardiac surgeries. Using a detailed data set of more than 5,600 cardiac surgeries in a large hospital, we quantify how surgeon's daily workload level (e.g., number of surgeries) affects surgery duration and patient outcomes. To handle the endogeneity of surgeon's daily workload, we construct instrument variables using hospital operational factors, including the block schedule of surgeons. We find high daily workload of surgeons is associated with longer incision times and worse patient outcomes. Specifically, increased daily workload of surgeons leads to longer post-surgery length-of-stay in ICU and hospital, as well as higher likelihoods of reoperation and readmission for their patients. These results highlight the potential negative impact of surgeon's fatigue under long working hours. We then develop a surgery scheduling model that incorporates the effects of surgeon's daily workload levels.

No description available.

Este trabajo de investigación se busca estimar el impacto que tiene el precio del cobre sobre la dinámica de los créditos al sector privado en la economía peruana. La literatura nos muestra que el crecimiento del crédito desmesurado puede debilitar el sistema financiero en una economía y más aún si esta depende de la exportación de commodities. El efecto de los denominados booms de commodities suelen llevar a incrementos atípicos en el crédito otorgado al sector privado. Este comportamiento a largo y mediano plazo puede conducir a crisis financieras. Para el caso del Perú, no solo se sigue el modelo primario exportador, sino que también se ha registrado en su economía un crecimiento persistente en los créditos otorgados al sector privado a lo largo de casi 20 años. Sumado a esto, la incertidumbre provocada por la guerra comercial EE. UU y China ha impactado en los precios de los commodities y la balanza comercial peruana ya que ha disminuido la demanda de cobre, la exportación principal del Perú, del gigante asiático, su mayor comerciante. Cabe resaltar que en este trabajo no se está tomando en consideración los posibles efectos de la actual crisis sanitaria causada por el SARS-CoV-2 (COVID-19). Dada la literatura sobre los orígenes de las crisis financieras y la coyuntura actual del Perú, se analizará el comportamiento del precio del cobre, commodity principal exportado del país, y su relación a largo plazo con el crédito total privado peruano. El periodo de análisis escogido es desde el 2004 hasta el primer trimestre del 2020 debido a que a partir de ese periodo es que el crédito demuestra un crecimiento inusual que se ha mantenido hasta la fecha. / This paper seeks to estimate the impact that the Price of the cooper has on the private credit Dynamic for the peruvian economy. Literature shows that excessive growth of private credit could have a negative effect on the financial system and it could be even worse if said economy is commodity dependent. The effect of the so called commodity boom usually leads to an unsual increase on the private credit. In the long run, if such behavior persists, it could end up in a financial crisis. For the peruvian case, not only are its economy commodity dependant but his economy has registered a persistent growth of the credit provided to the private sector for almost 20 years. Moreover, the uncertainty caused by the trade war between USA and China has impacted the prices of some of the most important commodities to Peru and therefore had negative implications on their comercial balance. Copper demand from China has decreased, copper been the main commodity exported by Perú and China its bigger partner. It should be noticed that this paper will not take in consideration the possible effects of the SARS-CoV-2 (COVID-19). By taking in consideration the literature about financial crisis and given the peruvian economic enviroment, in this work we will focus on analysing the intenational prices of cooper, main commodity exported by Peru, and it’s relationship with the private credit. Our time period will be from 2004 to the first quarter of 2020. / Trabajo de investigación

This study analyzes the effectiveness of the Cooperatives Working Together (CWT) program. This program is believed to have improved the farm-level price of milk since it began in July 2003. To date, no publicly available analysis addressing this question has been conducted. Total milk removed by the program was determined and expressed as a percentage of total milk produced nationally during the same time frame. Elasticity measures from prior studies were adapted to determine the impact of the program. This analysis suggests the program has had a significantly positive effect on the price of milk. Issues dealing with future action were identified and discussed. In addition to analyzing the effectiveness of the CWT program, a survey was conducted among Utah dairy producers who had recently exited the industry. It was determined that the majority of these producers were older and did not exit through the CWT program. The primary reasons for their exit were their older age, low milk prices, and lack of family interest in continuing to operate the dairy.

We aim to identify factors that are critical in determining whether or not blockchain adoption arises in various market structures, and give guidance for addressing the challenges of blockchain implementation. In Chapter 2, we construct an economic framework for understanding the incentives of the firms in a supply chain to form a blockchain consortium. We find that blockchain reduces information asymmetry for consumers, thereby enhancing consumer welfare. Consumer welfare gains can be sufficiently large that blockchain adoption is socially beneficial; nonetheless, we find that blockchain adoption does not arise in equilibrium. This situation arises because blockchain adoption costs are borne by manufacturers, and manufacturers cannot extract consumer gains through prices due to the competitive nature of the manufacturing sector. We offer a system of transfers to generate blockchain adoption in equilibrium when it is socially beneficial. In Chapter 3, we investigate a variation of the model described in Chapter 2. Our analysis incorporates the blockchain’s ability to trace shipments and generate cost savings for the manufacturers who join the blockchain. Although the blockchain enables early recalls of defective goods with higher probability, and thus, reduces expected unit costs for all the manufacturers on the blockchain, such gains are still competed away and blockchain adoption does not arise in equilibrium. This result strengthens our earlier findings on the incentive misalignment in a perfectly competitive setting. The associated welfare implications of this model are similar to those in Chapter 2. In Chapter 4, we study a setting in which the consumer prices are determined exogenously. With this setting of sticky price, there exists a certain level of competition but it is not perfect. As a result, the manufacturer gains from blockchain adoption may be strictly positive, in contrast to two results in Chapters 2 and 3 where the gains are always competed away. We find that blockchain unequivocally benefits consumers but has an ambiguous effect upon the welfare of manufacturers. There exist conditions under which, although the blockchain improves global welfare, blockchain adoption does not arise in equilibrium. We refer to such a scenario as an adoption failure, and again a system of transfers is proposed to resolve that failure. In Chapter 5, we examine whether blockchain adoption arises in equilibrium for a supply chain in which a single risk-averse manufacturer sells directly to consumers; thus, the manufacturer possesses market power. In this setting, we find that blockchain adoption always enhances manufacturer welfare when the adoption cost is zero. While two results in Chapters 2 and 3 demonstrate that blockchain adoption does not arise when the manufacturing sector is perfectly competitive, our findings clarify that the failure of blockchain adoption is not generic across all market structures. Rather, blockchain adoption arises in equilibrium for supply chains when the manufacturer possesses market power and when the adoption cost is sufficiently small.