pwc-archive/papers-with-abstracts huggingface dataset:
Macroeconomic Spillovers of Weather Shocks across U.S. States
Authors: Emanuele Bacchiocchi, Andrea Bastianin, Graziano Moramarco
Date: 2024-03-16 00:00:00

We estimate the short-run effects of severe weather shocks on local economic activity and cross-border spillovers operating through economic linkages between U.S. states. We measure weather shocks using emergency declarations triggered by natural disasters and estimate their impacts with a monthly Global Vector Autoregressive (GVAR) model for U.S. states. Impulse responses highlight country-wide effects of weather shocks hitting individual regions. Taking into account economic interconnections between states allows capturing much stronger spillovers than those associated with mere spatial adjacency. Also, geographical heterogeneity is critical for assessing country-wide effects of weather shocks, and network effects amplify the local impacts of shocks.
Testing Goodness-of-Fit for Conditional Distributions: A New Perspective based on Principal Component Analysis
Authors: Cui Rui, Li Yuhao
Date: 2024-03-15 00:00:00

This paper introduces a novel goodness-of-fit test technique for parametric conditional distributions. The proposed tests are based on a residual marked empirical process, for which we develop a conditional Principal Component Analysis. The obtained components provide a basis for various types of new tests in addition to the omnibus one. Component tests that based on each component serve as experts in detecting certain directions. Smooth tests that assemble a few components are also of great use in practice. To further improve testing performance, we introduce a component selection approach, aiming to identify the most contributory components. The finite sample performance of the proposed tests is illustrated through Monte Carlo experiments.
Multiscale Orientation Values for Biodiversity, Climate and Water: A Scientific Input for Science- Based Targets
Authors: Viktoras Kulionis, Andreas Froemelt, Stephan Pfister
Date: 2024-03-18 00:00:00

In this study, we explore a range of options and outcomes associated with using different allocation approaches to operationalise the Planetary Boundaries (PB) framework at the country, sector, and city scales. We demonstrate: (i) how to translate the PB framework into various sub-global scales (countries, cities, industries); and (ii) how to take global/local aspects (e.g., water use at the watershed level) into account. Finally, we apply the proposed methodology to derive country, city, and sector-specific budgets consistent with the PB concept for Switzerland. We then benchmark the translated PBs for climate, biodiversity, and freshwater use against actual environmental pressures in Switzerland from both production- and consumption-based perspectives. This effectively enables us to provide a comprehensive assessment of whether Switzerland is living within its safe operating space.
What Makes Systemic Discrimination, "Systemic?" Exposing the Amplifiers of Inequity
Authors: David B. McMillon
Date: 2024-03-16 00:00:00
Tasks: Sociology

Drawing on work spanning economics, public health, education, sociology, and law, I formalize theoretically what makes systemic discrimination "systemic." Injustices do not occur in isolation, but within a complex system of interdependent factors; and their effects may amplify as a consequence. I develop a taxonomy of these amplification mechanisms, connecting them to well-understood concepts in economics that are precise, testable and policy-oriented. This framework reveals that these amplification mechanisms can either be directly disrupted, or exploited to amplify the effects of equity-focused interventions instead. In other words, it shows how to use the machinery of systemic discrimination against itself. Real-world examples discussed include but are not limited to reparations for slavery and Jim Crow, vouchers or place-based neighborhood interventions, police shootings, affirmative action, and Covid-19.
How Periodic Forecast Updates Influence MRP Planning Parameters: A Simulation Study
Authors: Wolfgang Seiringer, Klaus Altendorfer, Thomas Felberbauer, Balwin Bokor, Fabian Brockmann
Date: 2024-03-16 00:00:00

In many supply chains, the current efforts at digitalization have led to improved information exchanges between manufacturers and their customers. Specifically, demand forecasts are often provided by the customers and regularly updated as the related customer information improves. In this paper, we investigate the influence of forecast updates on the production planning method of Material Requirements Planning (MRP). A simulation study was carried out to assess how updates in information affect the setting of planning parameters in a rolling horizon MRP planned production system. An intuitive result is that information updates lead to disturbances in the production orders for the MRP standard, and, therefore, an extension for MRP to mitigate these effects is developed. A large numerical simulation experiment shows that the MRP safety stock exploitation heuristic, that has been developed, leads to significantly improved results as far as inventory and backorder costs are concerned. An interesting result is that the fixed-order-quantity lotsizing policy performs - in most instances - better than the fixed-order-period lotsizing policy, when periodic forecast updates occur. In addition, the simulation study shows that underestimating demand is marginally more costly than overestimating it, based on the comparative analysis of all instances. Furthermore, the results indicate that the MRP safety stock exploitation heuristic can mitigate the negative effects of biased forecasts.
Financial Performance and Innovation: Evidence From USA, 1998 - 2023
Authors: Panteleimon Kruglov, Charles Shaw
Date: 2024-03-16 00:00:00

This study explores the relationship between R&D intensity, as a measure of innovation, and financial performance among S&P 500 companies over 100 quarters from 1998 to 2023, including multiple crisis periods. It challenges the conventional wisdom that larger companies are more prone to innovate, using a comprehensive dataset across various industries. The analysis reveals diverse associations between innovation and key financial indicators such as firm size, assets, EBITDA, and tangibility. Our findings underscore the importance of innovation in enhancing firm competitiveness and market positioning, highlighting the effectiveness of countercyclical innovation policies. This research contributes to the debate on the role of R&D investments in driving firm value, offering new insights for both academic and policy discussions.
Gentrification, displacement, and income trajectory of incumbents
Authors: Pierre-Loup Beauregard
Date: 2024-03-15 00:00:00

Gentrification is associated with rapid demographic changes within inner-city neighborhoods. While many fear that gentrification drives low-income people from their homes and communities, there is limited evidence of the consequences of these changes. I use Canadian administrative tax files to track the movements of incumbent workers and their income trajectory as their neighborhood gentrifies. I exploit the timing at which neighborhoods gentrify in a matched staggered event-study framework. I find no evidence of displacement effects, even for low socioeconomic status households. In fact, families living in gentrifying neighborhoods are more likely to stay longer. I suggest that this might be related to tenant rights protection laws. When they endogenously decide to leave, low-income families do not relocate to worse neighborhoods. Finally, I find no adverse effects on their income trajectory, suggesting no repercussions on their labor market outcomes.
Global Shipyard Capacities Limiting the Ramp-Up of Global Hydrogen Transport
Authors: Maximilian Stargardt, David Kress, Heidi Heinrichs, Jörn-Christian Meyer, Jochen Linßen, Grit Walther, Detlef Stolten
Date: 2024-03-14 00:00:00

Decarbonizing the global energy system requires significant expansions of renewable energy technologies. Given that cost-effective renewable sources are not necessarily situated in proximity to the largest energy demand centers globally, the maritime transportation of low-carbon energy carriers, such as renewable-based hydrogen or ammonia, will be needed. However, whether existent shipyards possess the required capacity to provide the necessary global fleet has not yet been answered. Therefore, this study estimates global tanker demand based on projections for global hydrogen demand, while comparing these projections with historic shipyard production. Our findings reveal a potential bottleneck until 2033-2039 if relying on liquefied hydrogen exclusively. This bottleneck could be circumvented by increasing local hydrogen production, utilizing pipelines, or liquefied ammonia as an energy carrier for hydrogen. Furthermore, the regional concentration of shipyard locations raises concerns about diversification. Increasing demand for container vessels could substantially hinder the scale-up of maritime hydrogen transport.
Prediction of retail chain failure: examples of recent U.S. retail failures
Authors: Shawn Berry
Date: 2024-03-14 00:00:00

Over the last several years, several well-established and prominent brick-and-mortar retail chains have ceased operations, raising concerns for something that some have referred to as a retail apocalypse. While the demise of brick-and-mortar is far from certain, scholars have attempted to model the likelihood that a retailer is about to fail using different approaches. This paper examines the failures of Bed Bath and Beyond, J.C. Penney, Rite Aid, and Sears Holdings in the United States between 2013 and 2022. A model of retail failure is presented that considers internal and external firm factors using both annual report and macroeconomic data. The findings suggest that certain revenue-based financial ratios and the annual average U.S. inflation rates are statistically significant predictors of failure. Furthermore, the failure model demonstrated that it can provide a nontrivial early warning signal at least the year before failure. The paper concludes with a discussion and directions for future research.
Climate Immobility Traps: A Household-Level Test
Authors: Marco Letta, Pierluigi Montalbano, Adriana Paolantonio
Date: 2024-03-14 00:00:00

The complex relationship between climate shocks, migration, and adaptation hampers a rigorous understanding of the heterogeneous mobility outcomes of farm households exposed to climate risk. To unpack this heterogeneity, the analysis combines longitudinal multi-topic household survey data from Nigeria with a causal machine learning approach, tailored to a conceptual framework bridging economic migration theory and the poverty traps literature. The results show that pre-shock asset levels, in situ adaptive capacity, and cumulative shock exposure drive not just the magnitude but also the sign of the impact of agriculture-relevant weather anomalies on the mobility outcomes of farming households. While local adaptation acts as a substitute for migration, the roles played by wealth constraints and repeated shock exposure suggest the presence of climate-induced immobility traps.
Zonal vs. Nodal Pricing: An Analysis of Different Pricing Rules in the German Day-Ahead Market
Authors: Johannes Knörr, Martin Bichler, Teodora Dobos
Date: 2024-03-14 00:00:00

The European electricity market is based on large pricing zones with a uniform day-ahead price. The energy transition leads to changes in supply and demand and increasing redispatch costs. In an attempt to ensure efficient market clearing and congestion management, the EU Commission has mandated the Bidding Zone Review (BZR) to reevaluate the configuration of European bidding zones. Based on a unique data set published in the context of the BZR for the target year 2025, we analyze the short-run effects of various pricing rules for the German-Luxembourgish bidding zone. We compare market clearing and pricing for different zonal models, including their generation and redispatch costs. In numerical experiments with this dataset, the differences in the average prices in different zones are low. The total costs across different configurations are similar and the reduction of standard deviations in prices is also small. This might be different with other load and generation scenarios, but the BZR data is important as it was created to make a decision about splits of the existing bidding zones. We can replicate several results from the BZR study, except the large cost savings when moving from one to two price zones in Germany and Luxembourg. In addition to the four zonal configurations analyzed in the BZR study, we compare these against a nodal pricing system. While the total cost savings after introducing zonal splits were less than 1%, nodal pricing led to savings of 5-6%. We also evaluate differences of nodal pricing rules with respect to the necessary uplift payments, which is relevant in the context of the discussion on non-uniform pricing in the EU. While the study focuses on Germany, the analysis is relevant beyond and feeds into the broader discussion about pricing rules in non-convex markets.
Study on Standardizing Working Time: A Case of XYZ Retail Store in Bandung, Indonesia
Authors: Aprodhita Anindya Putri, Akhmad Yunani
Date: 2024-03-14 00:00:00

Work time standardization helps to find and reduce wasteful movements and time in the workplace, such as chatting, mobile phone use, insufficient rest, or unproductive tasks. This study aims to map the process of displaying products from the warehouse to the shelves and calculate and determine the standard working time of employees of the Operations Division of PT XYZ Branch who oversee displaying X Milk and Y Bread. The data was collected six times in three weeks, including interviews and observations, and took a sample of 20 pieces on each product to carry out data analysis such as data sufficiency tests and control charts. Several time deviations were found in the display process of X Milk products on all observation days in different activities. Whereas in the process of displaying Y Bread, only the deviation of working time was found on the 4th observation day, which proves that the process needs to have a standard working time so that the activity work time is more controlled. Therefore, the analysis is carried out with the calculation of performance rating, time allowance, normal time, and standard time. The result of the standard time calculation for the display process of X Milk products is 15.83 minutes and Y Bread is 9.18 minutes for each product of 20 units.
Entangled vs. Separable Choice
Authors: Nail Kashaev, Martin Plávala, Victor H. Aguiar
Date: 2024-03-14 00:00:00
Tasks: Decision Making

We investigate joint probabilistic choice rules describing the behavior of two decision makers, each facing potentially distinct menus. These rules are separable when they can be decomposed into individual choices correlated solely through their respective probabilistic choice rules. Despite its significant interest for the study of peer effects, influence, and taste variation, a complete characterization of these rules has remained elusive (Chambers, Masatlioglu, and Turansick, 2021). We fully characterize separable choices through a finite system of inequalities inspired by Afriat's theorem. Our results address the possibility of entangled choices, where decision makers behave as if they do not communicate, yet their choices are not separable. More generally, we establish that separable joint choice restrictions can be factored into individual choice restrictions if only if at least one decision maker's probabilistic choice rule uniquely identifies the distribution over deterministic choice rules. The no communication condition and the individual restrictions are no longer sufficient in the absence of this uniqueness. Our results offer robust tools for distinguishing between separable decision-making and behaviors beyond mere peer effects such as imitation and cheating.
Measuring the bioeconomy economically: exploring the connections between concepts, methods, data, indicators and their limitations
Authors: Sebastián Leavy, Gabriela Allegretti, Elen Presotto, Marco Antonio Montoya, Edson Talamini
Date: 2024-03-13 00:00:00
Tasks: Articles

Despite its relevance, measuring the contributions of the bioeconomy to national economies remains an arduous task that faces limitations. Part of the difficulty is associated with the lack of a clear and widely accepted concept of the bioeconomy and moves on to the connections between methods, data and indicators. The present study aims to define the concepts of bioeconomy and to explore the connections between concepts, methods, data and indicators when measuring the bioeconomy economically, and the limitations involved in this process. The bioeconomy concepts were defined based on a literature review and a content analysis of 84 documents selected through snowballing procedures to find articles measuring 'how big is the bioeconomy?'. The content of the 84 documents was uploaded to the QDA Miner software and coded according to the bioeconomy concept, the methods or models used, the data sources accessed, the indicators calculated, and the limitations reported by the authors. The results of the occurrence and co-occurrence of the codes were extracted and analyzed statistically, indicating that the measurement of bioeconomy (i) need recognize and pursue the proposed concept of holistic bioeconomy; (ii) rarely considered aspects of holistic bioeconomy (3.5%); (iii) is primarily based on the concept of biomass-based bioeconomy (BmBB) (94%); (iv) the association with the concept of biosphere (BsBB) appeared in 26% of the studies; (v) the biotech-based bioeconomy (BtBB) was the least frequent (1.2%); (vi) there is a diversity of methods and models, but the most common are those traditionally used to measure macroeconomic activities, especially input-output models; (vii) depending on the prevailing methods, the data comes from various official statistical databases, such as national accounts and economic activity classification systems;...
Valuation of Power Purchase Agreements for Corporate Renewable Energy Procurement
Authors: Roozbeh Qorbanian, Nils Löhndorf, David Wozabal
Date: 2024-03-13 00:00:00

Corporate renewable power purchase agreements (PPAs) are long-term contracts that enable companies to source renewable energy without having to develop and operate their own capacities. Typically, producers and consumers agree on a fixed per-unit price at which power is purchased. The value of the PPA to the buyer depends on the so called capture price defined as the difference between this fixed price and the market value of the produced volume during the duration of the contract. To model the capture price, practitioners often use either fundamental or statistical approaches to model future market prices, which both have their inherent limitations. We propose a new approach that blends the logic of fundamental electricity market models with statistical learning techniques. In particular, we use regularized inverse optimization in a quadratic fundamental bottom-up model of the power market to estimate the marginal costs of different technologies as a parametric function of exogenous factors. We compare the out-of-sample performance in forecasting the capture price using market data from three European countries and demonstrate that our approach outperforms established statistical learning benchmarks. We then discuss the case of a photovoltaic plant in Spain to illustrate how to use the model to value a PPA from the buyer's perspective.
Speed, Accuracy, and Complexity
Authors: Duarte Gonçalves
Date: 2024-03-17 00:00:00

This paper re-examines the use of response time to infer problem complexity. It revisits a canonical Wald model of optimal stopping, taking signal-to-noise ratio as a measure of problem complexity. While choice quality is monotone in problem complexity, expected stopping time is inverse U-shaped. Indeed, decisions are fast in both very simple and very complex problems: in simple problems, it is quick to understand which alternative is best, while in complex problems it would be too costly -- an insight which extends to general costly information acquisition models. This non-monotonicity also underlies an ambiguous relationship between response time and ability, whereby higher ability entails slower decisions in very complex problems, but faster decisions in simple problems. Finally, this paper proposes a new method to correctly infer problem complexity based on the finding that distorting incentives in favour of an alternative has a greater effect on choices in more complex problems.
Irrational Random Utility Models
Authors: Daniele Caliari, Henrik Petri
Date: 2024-03-15 00:00:00

The Random Utility Model (RUM) is the leading model to represent the aggregate choices of a heterogeneous population of preference maximizers. We show that if (and only if) preferences are sufficiently uncorrelated, RUM choices can also be generated by a population of decision makers who do not maximize any preference. In proving this result, we also characterize the general class of choices generated by such irrational populations, with applications beyond the RUM framework. We discuss the relevance of our results for the falsifiability of the rational interpretation of RUMs, the inference of individual rationality from aggregate choices, and the nature of welfare judgments.
News Media as Suppliers of Narratives (and Information)
Authors: Kfir Eliaz, Ran Spiegler
Date: 2024-03-14 00:00:00

We present a model of news media that shape consumer beliefs by providing information (signals about an exogenous state) and narratives (models of what determines outcomes). To amplify consumers' engagement, media maximize consumers' anticipatory utility. Focusing on a class of separable consumer preferences, we show that a monopolistic media platform facing homogenous consumers provides a false "empowering" narrative coupled with an optimistically biased signal. Consumer heterogeneity gives rise to a novel menu-design problem due to a "data externality" among consumers. The optimal menu features multiple narratives and creates polarized beliefs. These effects also arise in a competitive media market model.
AdaMER-CTC: Connectionist Temporal Classification with Adaptive Maximum Entropy Regularization for Automatic Speech Recognition
Authors: SooHwan Eom, Eunseop Yoon, Hee Suk Yoon, Chanwoo Kim, Mark Hasegawa-Johnson, Chang D. Yoo
Date: 2024-03-18 00:00:00
Tasks: Automatic Speech Recognition, Automatic Speech Recognition (ASR), speech-recognition, Speech Recognition

In Automatic Speech Recognition (ASR) systems, a recurring obstacle is the generation of narrowly focused output distributions. This phenomenon emerges as a side effect of Connectionist Temporal Classification (CTC), a robust sequence learning tool that utilizes dynamic programming for sequence mapping. While earlier efforts have tried to combine the CTC loss with an entropy maximization regularization term to mitigate this issue, they employed a constant weighting term on the regularization during the training, which we find may not be optimal. In this work, we introduce Adaptive Maximum Entropy Regularization (AdaMER), a technique that can modulate the impact of entropy regularization throughout the training process. This approach not only refines ASR model training but ensures that as training proceeds, predictions display the desired model confidence.