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on Regulation |
| By: | Wolfgang Briglauer (Vienna University of Economics and Business (WU)); Michał Grajek (ESMT European School of Management and Technology) |
| Abstract: | The deployment of new broadband networks (NBNs) based on fiber-optic transmission technologies promises high gains in terms of productivity and economic growth, and has attracted subsidies worth billions from governments around the world in the form of various state aid programs. Yet, the effectiveness and the efficiency of such programs remains largely unstudied. We employ panel data from 32 OECD countries during 2002-2019 to provide robust empirical evidence of both. We find that state aid significantly increases NBNs by facilitating the deployment of new connections to 22% of households in the short term and 39.2% in the long term. By comparing the actual amounts of state aid support to the estimated impact on GDP growth, we also find it to be highly cost efficient, as the programs break even after three years on average. |
| Keywords: | Fiber optic technology, state aid, ex-post evaluation, efficiency, OECD countries |
| JEL: | C51 C54 H25 L52 O38 |
| Date: | 2021–08–23 |
| URL: | http://d.repec.org/n?u=RePEc:esm:wpaper:esmt-21-01&r= |
| By: | Iwan Bos (Department of Organisation, Strategy and Entrepreneurship, Maastricht University); Marco A. Marini (Department of Social and Economic Sciences, Sapienza University of Rome); Riccardo D. Saulle (Department of Economics and Management, University of Padova) |
| Abstract: | This paper examines capacity-constrained oligopoly pricing with sellers who seek myopic improvements. We employ the Myopic Stable Set stability concept and establish the existence of a unique pure-strategy price solution for any given level of capacity. This solution is shown to coincide with the set of pure-strategy Nash equilibria when capacities are large or small. For an intermediate range of capacities, it predicts a price interval that includes the mixed-strategy support. This stability concept thus encompasses all Nash equilibria and offers a pure-strategy solution when there is none in Nash terms. In particular, it provides a behavioral rationale for different types of pricing dynamics, including real-world economic phenomena such as Edgeworth-like price cycles, price dispersion and supply shortages. |
| Keywords: | Behavioral IO, Bounded Rationality, Capacity Constraints, Oligopoly Pricing, Myopic Stable Set |
| JEL: | C72 D43 L13 |
| Date: | 2021–03 |
| URL: | http://d.repec.org/n?u=RePEc:pad:wpaper:0271&r= |
| By: | Kevin A. Bryan; Heidi L. Williams |
| Abstract: | This is an invited chapter for the forthcoming Volume 4 of the Handbook of Industrial Organization. We summarize the state of the literature on the economics of innovation and highlight open policy questions. We first articulate the key market failures in markets for innovation, and then discuss how both scientific norms and market-oriented policies help overcome those market failures. We close by discussing recent work on the diffusion of inventions as well as on the links between innovation and inequality. |
| JEL: | O3 |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:29173&r= |
| By: | Boeing, Geoff (Northeastern University); Besbris, Max; Wachsmuth, David; Wegmann, Jake |
| Abstract: | This article interprets emerging scholarship on rental housing platforms—particularly the most well-known and used short- and long-term rental housing platforms—and considers how the technological processes connecting both short-term and long-term rentals to the platform economy are transforming cities. It discusses potential policy approaches to more equitably distribute benefits and mitigate harms. We argue that information technology is not value-neutral. While rental housing platforms may empower data analysts and certain market participants, the same cannot be said for all users or society at large. First, user-generated online data frequently reproduce the systematic biases found in traditional sources of housing information. Evidence is growing that the information broadcasting potential of rental housing platforms may increase rather than mitigate sociospatial inequality. Second, technology platforms curate and shape information according to their creators' own financial and political interests. The question of which data—and people—are hidden or marginalized on these platforms is just as important as the question of which data are available. Finally, important differences in benefits and drawbacks exist between short-term and long-term rental housing platforms, but are underexplored in the literature: this article unpacks these differences and proposes policy recommendations. |
| Date: | 2021–08–21 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:8jrfe&r= |
| By: | Haataja, Meeri; Bryson, Joanna J. (Hertie School) |
| Abstract: | This short analysis aims to provide an overview of the anticipated costs caused by the EU’s proposed AI regulation, the AI Act (AIA), to impacted organisations: both providers and deployers of systems containing AI. We focus our analysis at an enterprise level, leaving the macroeconomic discussion for later. While the bulk of the paper explains and critiques the European Commission’s (EC) own analysis we also comment on the critiques raised recently by a high-profile US lobbyist, the Center for Data Innovation, in their report “How Much Will the Artificial Intelligence Act Cost Europe?” We conclude by highlighting topics that would benefit from further elaboration by the EC. As a reminder, the AIA is presently draft legislation, written by the European Commission. While something quite similar can be expected to be implemented ultimately by the European Union’s member states, the legislation is presently in a period of revision by the elected members of the European Parliament, in cooperation and consultation with EU national governments. While the heart of the EU’s regulatory proposal is in safeguarding people against AI risks to health, safety and fundamental rights, we acknowledge the importance of rooting policies in a sound analysis of financial impacts. It is only that way that requirements get translated into solid action plans and finally into actions. The process of such pragmatic analysis, can also get at assumptions and failures of coherence that might otherwise be overlooked. We also, separately, have a longer commentary on the act itself, see “Reflections on the EU’s AI Act and how we could make it even better.” Our analysis of the AIA costs is based on the two main sources: the EC’s Impact Assessment of the AIA, and the EC’s study to support an impact assessment of regulatory requirements for artificial intelligence in Europe. It is noteworthy that while the EC uses the support study as its main source for financial impact assessment, in some contexts, they specifically choose to interpret the figures differently, e.g. by excluding some categories of costs from the impact assessment. For this, it is critical to treat the EC’s impact assessment and the support study as two separate sources. This was one of a number of things apparently missed by the Center for Data Innovation in their report. |
| Date: | 2021–08–27 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:8nzb4&r= |
| By: | Robert Clark; Jean-François Houde; Jakub Kastl |
| Abstract: | This chapter discusses recent developments in the literature involving applications of industrial organization methods to finance. We structure our discussion around a simple model of a financial intermediary that concentrates its attention either on (i) the retail market and hence engages in a traditional maturity transformation business by accepting funds that can be used to invest in risky projects (loans), or (ii) the investment business, financing its operations on the “wholesale” market and making markets or investing in higher return riskier projects. Our discussion is centered around the analysis of market structure and competition in each of these markets, focusing in turn on (i) primary and secondary markets for government and corporate debt, (ii) interbank loans, (iii) markets for retail funding, and (iv) credit markets, including mortgages. |
| JEL: | G2 L1 L51 |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:29183&r= |
| By: | Selim Banabak |
| Abstract: | Although there exists some scientific literature concerned with pricing on the Austrian real estate market (Helbich, W. Brunauer, et al., 2014; Kuntz and Helbich, 2014; W. Brunauer, Lang, and Umlauf, 2013), there is surprisingly little quantitative research on housing rents, their spatial structure and drivers. Expanding the existing literature beyond house price prediction is especially important in the Viennese case, where according to the Austrian Mikrozensus, 77.5% of the population live in a rented flat (Statistik Austria, 2020). Thus, quantitative research on the Austrian housing market cannot primarily focus on price formation regarding private real estate property but needs to also consider rental markets. W. A. Brunauer et al. (2010) provide a notable exception from the lack of quantitative research on the Viennese rental case as well as an interesting approach using a Generalized Additive Model with spatial scaling. Fortunately, there is also a growing body of econometric literature on housing rents and their drivers onthe international stage where one could draw ideas from. Recent examples can be found in Tomal (2020); McCord et al. (2014) or Efthymiou and Antoniou (2013.) Usually in the spirit of hedonic house price models, housing rents are regressed onto certain characteristics of the respective flat as well as some indicators measuring the quality of location. However, the Viennese housing market has several special features which have not been properly addressed in housing rent modeling up till now. An important feature of the Viennese accommodation market is the fact that roughly 43% of households live in a flat provided by the social sector, which consists of municipal as well as cooperative (non-profit) housing. The private rental sector on the other hand accommodates about a third of the households (Tockner, 2017). Thus, dynamics in the comparatively small free market segment cannot be adequately understood if considered independent from the larger social sector (Kemeny,Kersloot, and Thalmann, 2005). A further important aspect is the strong regulation of rent prices through the Mietrechtsgesetz (MRG) that basically constitutes two regulatory regimes within the private market segment. On the one hand flats located in buildings erected before 1945 or built with state subsidies experience strong price controls. On the other hand, flats that do not fulfill the previously mentioned criteria as well as single family houses do not experience any such price controls. However, the introduction of location bonuses to the price-controlled segment led to spatially very uneven price increases over the last years (Kadi, 2015). We propose a hierarchical generalized additive model (HGAM) to model squaremeter prices by smooth functions of flat characteristics such as size, age, and time within the sample. Additionally, various dummy variables enter the model as linear predictors and random effects are used to model subdistrict specific location bonuses in the baseline model. Going beyond the existing hedonic housing rent literature this study also proposes several extensions to model, addressing the aforementioned special features of the Viennese rental market. Thus, the baseline HGAM is modified to incorporate regulatory-regime heterogeneity in its parameters as well as spatial heterogeneity with respect to time trends in order to properly address the differences in the development of location bonuses. Varying degree of competition from the social sector in each subdistrict is also tested as a potential impacting factor onto rents. As spatial autocorrelation might be an issue given the spatial nature of the data, we do not only use random effects for the location bonuses but also add a spatially structured predictor using markov-random-fields. The Data available for this study was kindly provided by the DataScience Service GmbH and consists of over 84,000 observations of flats offered on the Viennese rental market between 2012 and 2020 with a very high coverage rate during the more recent years. Asking prices, GIS data, very detailed real estate characteristics including size, age, furnishing and many more, as well as a multitude of socio-economic variables on the respective area such as share of academics, proximity to medical infrastructure or accessibility of public transport are available for the given dataset. Due to the constant excess demand on the accommodation market in Vienna for the given period, asking prices are assumed to hardly deviate from market prices and can be seen, as a legitimate approximation. First results suggest that all proposed extensions to the baseline model add significant predictive power. |
| Keywords: | HGAM; Housing Rents; Rent Regulation; Vienna |
| JEL: | R3 |
| Date: | 2021–01–01 |
| URL: | http://d.repec.org/n?u=RePEc:arz:wpaper:eres2021_167&r= |
| By: | Jenn, Alan; Brown, Austin |
| Abstract: | California has goals of achieving 100% renewable energy by 2045 and 100% zero-emission vehicle sales by 2035. Electric vehicles will introduce significant new demand for electricity at the same time the state’s electricity grid is incorporating more intermittent energy sources, raising concerns about grid reliability. However, the flexibility of electric vehicle charging provides a potentially powerful asset in mitigating the challenges of a renewable energybased electricity grid. Smart charging—adapting electric vehicle charging based on the conditions of the power system and the needs of the vehicle user—can take advantage of this flexibility by charging vehicles when renewable energy is readily available. Researchers at UC Davis simulated 100% electric vehicle adoption and a 100% renewable energy-powered electricity grid by 2045 in California. They then compared a scenario of regular electric vehicle charging behavior with a scenario of advanced, flexible, smart charging under which charging is aligned with renewable energy availability, to understand how smart vehicle charging could benefit the electricity grid. |
| Keywords: | Social and Behavioral Sciences |
| Date: | 2021–08–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt5rf8b4hz&r= |
| By: | Tije van Casteren; Ioulia Ossokina; Theo Arentze |
| Abstract: | In the coming decades, many countries need to improve the energy efficiency of their building stock, to realize the climate and renewable energy goals. In the Netherlands, this involves more than 5 million dwellings and many billions euros in costs. A considerable part of these costs has to be carried by home owners, and the challenge is to motivate them to timely invest in energy retrofitting. Households experience various barriers on their way to energy retrofitting of homes. Most prominent are: a high cost of gathering and verifying the information, financial constraints, risk aversion (Gerarden et al, 2017, Busse et al., 2013, Allcott and Wozny, 2014, Cattaneo, 2019). In the recent years various attempts have been made to address these barriers exploiting the possibilities of new digital communication technologies. Supported by (local) governments, new online platforms provide home owners looking for energy-efficiency investments with different services. These include: tailor-made advice on best energy-efficiency investments in specific homes; preselection of suppliers of a certain chosen technology (e.g. insulation, solar panels, high return boilers); setting up a collective purchase campaign for a neighbourhood, etc. There exists a small literature studying the effectiveness of online platforms in reducing consumer search and verification costs for products (Goldfarb and Tucker, 2019). For various domains (airlines, book stores, holiday homes) studies show that digital environments increase the share of successful matches between customers and suppliers. Still, not much is known yet to what degree this also holds for digital platforms that support purchasing of new home energy technologies. Further, little attention has been given so far to the heterogeneity of the consumers: for which groups of customers online platforms work well or for which not. Our study aims to fill these two knowledge gaps. We exploit unique data from a Dutch online platform that supports home owners in their collective purchase of various energy efficient home technologies. The data include information on some 10.000 platform participants and 300 collective purchase campaigns during the period 2013-2020. The data are merged on household level to the restricted access information about the socio-economic characteristics of the households and to their energy consumption. We study the determinants of the energy-efficiency investment choices households make on the platforms. These determinants include: the socio-economic characteristics of the households, their energy consumption pattern, the type of energy-efficient technology that is being purchased, etc. This paper has practical implications. Research shows that households differ in their energy consumption patterns and in their attitude towards energy transition (e.g. Albert and Maasoumy, 2016; Motlagh et al., 2019; Ossokina et al., 2020). It is therefore important to provide customized information to the consumers and select precise tools for specic household groups. Our study provides insights on how to do this using online environments that are being used more and more to support and stimulate energy transition in homes. |
| Keywords: | digital environments; effect measurement; energy-efficient investments in homes; microeconometrics |
| JEL: | R3 |
| Date: | 2021–01–01 |
| URL: | http://d.repec.org/n?u=RePEc:arz:wpaper:eres2021_110&r= |
| By: | Steuer, Sebastian; Tröger, Tobias |
| Abstract: | We study the design features of disclosure regulations that seek to trigger the green transition of the global economy and ask whether such regulatory interventions are likely to bring about sufficient market discipline to achieve socially optimal climate targets. We categorize the transparency obligations stipulated in green finance regulation as either compelling the standardized disclosure of raw data, or providing quality labels that signal desirable green characteristics of investment products based on a uniform methodology. Both categories of transparency requirements canbe imposed at activity, issuer, and portfolio level. Finance theory and empirical evidence suggest that investors may prefer "green" over "dirty" assets for both financial and non-financial reasons and may thus demand higher returns from environmentally-harmful investment opportunities. However, the market discipline that this negative cost of capital effect exerts on "dirty" issuers is potentially attenuated by countervailing investor interests and does not automatically lead to socially optimal outcomes. Mandatory disclosure obligations and their (public) enforcement can play an important role in green finance strategies. They prevent an underproduction of the standardized high-quality information that investors need in order to allocate capital according to their preferences. However, the rationale behind regulatory intervention is not equally strong for all categories and all levels of "green" disclosure obligations. Corporate governance problems and other agency conflicts in intermediated investment chains do not represent a categorical impediment for green finance strategies. However, the many forces that may prevent markets from achieving socially optimal equilibria render disclosure-centered green finance legislation a second best to more direct forms of regulatory intervention like global carbon taxation and emissions trading schemes. Inherently transnational market-based green finance concepts can play a supporting role in sustainable transition, which is particularly important as long as first-best solutions remain politically unavailable. |
| Keywords: | green finance,sustainable finance,ESG,mandatory disclosure,taxonomies,benchmarks,labels,asset pricing,market discipline,climate change,climate risk |
| JEL: | D4 D6 G1 G3 G4 K2 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:safewp:320&r= |
| By: | Donna, Javier D.; Espin-Sanchez, Jose-A. |
| Abstract: | We investigate the efficiency of a market relative to a non-market institution—an auction relative to a quota—as allocation mechanisms in the presence of frictions. We use data from water markets in southeastern Spain and explore a specific change in the institutions to allocate water. On the one hand, frictions arose because poor farmers were liquidity constrained. On the other hand, wealthy farmers who were part of the wealthy elite were not liquidity constrained. We estimate a structural dynamic demand model under the market by taking advantage that water demand for both types of farmers is determined by the technological constraint imposed by the crop’s production function. This approach allows us to differentiate liquidity constraints from unobserved heterogeneity. We use the estimated model to compute welfare under market and non-market institutions. We show that the institutional change from markets to quotas increased efficiency for the farmers considered. |
| Keywords: | Market Efficiency, Dynamic Demand, Auctions, Quotas, Vertical Integration, Financial Markets |
| JEL: | D02 G14 L11 L13 L42 L50 Q25 |
| Date: | 2021–04–05 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:109544&r= |
| By: | Franz Fuerst; Pat McAllister |
| Abstract: | The increasing policy emphasis on reducing carbon emissions has yielded a number of policies in various countries. In the UK, the Minimum Energy Efficiency Standard (MEES) made it illegal from April 2018 for landlords to let properties that did not meet a minimum energy performance standard - an Energy Performance Certificate (EPC) rating of E or higher. Although this policy has a relatively low cap on costs that landlords are expected to spend to upgrade their buildings, a dilemma for policy makers has been the trade-off between the compliance costs for owners and occupiers and potential improvements in energy consumption. An expected effect of introducing MEES is that improvements will be capitalised into the prices of properties. Implicitly, it is also expected that removing properties rated EPC F and G from the market will lead to changes to the relative demand and supply of policy compliant and non-compliant properties. The result is then increased demand for compliant properties and higher price differentials between compliant and non-compliant properties. Using a large dataset of residential sales transactions from 2009-2020, we study the price impact of MEES with a difference-in-difference approach and a regression discontinuity design. Our dataset allows us to compare the price trajectories of rental properties to the general housing market both before and after the introduction of the policy for the entire spectrum of energy efficient buildings. Although properties can hypothetically be switched between the owner-occupier and the private rental segments, we expect a stronger effect on the latter. Our research design also controls for a number of minor and major fiscal and regulatory changes since 2015 that have been introduced independently of MEES that could potentially distort the findings. |
| Keywords: | Energy Efficiency; Minimum Standards; Pricing of Residential Real Estate; Private Rental Market |
| JEL: | R3 |
| Date: | 2021–01–01 |
| URL: | http://d.repec.org/n?u=RePEc:arz:wpaper:eres2021_123&r= |
| By: | Arup Barua (South-Eastern Finland University of Applied Sciences, Finland); Alexandra Ioanid (University Politehnica of Bucharest, Romania) |
| Abstract: | The Resource-based View (RBV) and Industrial Organization (IO) theory have successfully clarified the competitive advantage for a single firm based on resources and market aspects but less so for knowing the competitive advantage for dual entities or companies. Therefore, this article attempts to investigate how a competitive advantage emerges in post-M&A. It illustrates that both theories together should contemplate the "synergistic competitive advantage" as a measurement of M&A performance, which explains the competitive advantage by the acquisition synergies, e.g., joint sales, expertise, revenue, and cost. The modern thought will widen the joint appeal of RBV and IO theory considering the SCP model because the synergy (i.e., a combined effect of two entities) should be a competitive, and competitive advantage should be synergistic for acquisition success. Future researchers are entreated to test the synergistic competitive advantage in post-M&A, evading the traditional competitive advantage. Decisively the implications and directions of future research would be illuminated. |
| Keywords: | RBV (Resource-based View), IO (Industrial Organization), SCP (Structure, Conduct, Performance), SCA (Synergistic Competitive Advantage), M&As (Mergers and Acquisitions) |
| JEL: | G34 M16 O19 |
| Date: | 2021–07 |
| URL: | http://d.repec.org/n?u=RePEc:sko:wpaper:bep-2021-06&r= |
| By: | Bakhtavoryan, Rafael; Hovhannisyan, Vardges |
| Keywords: | Resource/Energy Economics and Policy, Agricultural and Food Policy, Consumer/Household Economics |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea21:312650&r= |
| By: | Ruiz-Tagle, Cristobal; Schueftan, Alejandra |
| Abstract: | Air pollution from wood burning is a serious problem in the developing world. In the cities of south-central Chile, households experience extremely high ambient air pollution levels due to massive combustion of wood as fuel for residential heating. To address this problem, in recent years new residential wood stoves—equipped with improved combustion technologies that are designed to be less-polluting—have replaced high-polluting ones. However, users’ behaviour in operating these improved stoves is a key factor that drives actual emissions. When users ‘choke the damper’ to extend the burning time of their wood fuel, it constrains the air flow in the wood stoves and creates a highly polluting combustion process. To address this issue, a behavioural intervention was designed to provide users with real-time feedback on their wood stoves’ air pollution emissions with the goal of ‘nudging’ them to use their stoves in a less polluting way. The intervention consists of an information sign that aligns with the wood stove’s damper lever and informs users about pollution emission levels according to the chosen setting of the wood stove’s damper. The information sign is complemented by the visit of a field assistant that explains the sign and provides an informational flyer (fridge magnet). To assess the effectiveness of this behavioural intervention a randomized controlled trial was conducted with selected households in the city of Valdivia, Chile. Results from this intervention show that households that were provided with the information sign reduced the frequency with which they used the most polluting settings of their stoves, inducing a behavioural change that results in a 10.8% reduction in residential pollution emissions. |
| Keywords: | air pollution; behavioural intervention; environment and development; field experiment; wood stoves; Springer deal |
| JEL: | C93 D90 O13 Q53 Q56 |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:111527&r= |