Empirical Regularities Research Articles

A Simple Law for the Distribution of Long-Term Profit: The Empirical Regularity Behind the 1% of Firms That Capture 73% of Value

A Simple Law for the Distribution of Long-Term Profit: The Empirical Regularity Behind the 1% of Firms That Capture 73% of Value

A simple model of buyer–seller networks in international trade

The recent literature on firm-to-firm trade has documented salient empirical regularities of the buyer–seller network. We show that surprisingly many of these regularities emerge by superimposing the stochastic balls-and-bins structure of Armenter and Koren (2014) to firms in a classical Krugman (1980) model. Our approach amounts to a re-interpretation of Krugman (1980) and relies on randomized bundling of Krugman-varieties into heterogeneous firms, economically neutral ‘sales units’ that import foreign varieties but belong to local firms, and a statistical reporting threshold that applies to firm-to-firm transactions. We argue that our model provides an important benchmark for the assessment of theoretical models that aim to identify the determinants of firm-to-firm networks.

Rallying around the leader in times of crises: The opposing effects of perceived threat and anxiety

AbstractIn times of crisis, citizens tend to increase their approval of the government and its leader which can shift the balance of power. This ‘rally effect’ is a persistent empirical regularity; however, the literature is still undecided on its underlying causal mechanisms. We argue that crises induce threat and anxiety and hypothesize that perceived threat increases approval of the incumbent leader, whereas anxiety decreases it. By analysing German panel data from the COVID‐19 pandemic, we causally identify both mechanisms and provide systematic evidence supporting this theory. Moreover, we increase the scope of our theory and show that both mechanisms are also at work when citizens approve cabinet members who manage key portfolios. Our findings have highly important implications for our understanding of the rally effect and crises politics in democracies.

Exploring the Dynamic Behavior of Crude Oil Prices in Times of Crisis: Quantifying the Aftershock Sequence of the COVID-19 Pandemic

Crude oil prices crashed and dropped into negative territory at the onset of the COVID-19 pandemic. This extreme event triggered a series of great-magnitude aftershocks. We seek to investigate the cascading dynamics and the characteristics of the series immediately following the oil market crash. Utilizing a robust method named the Omori law, we quantify the correlations of these events. This research presents empirical regularity concerning the number of times that the absolute value of the percentage change in the oil index exceeds a given threshold value. During the COVID-19 crisis, the West Texas Intermediate (WTI) oil prices exhibit greater volatility compared to the Brent oil prices, with higher relaxation values at all threshold levels. This indicates that larger aftershocks decay more rapidly, and the period of turbulence for the WTI is shorter than that of Brent and the stock market indices. We also demonstrate that the power law’s exponent value increases with the threshold value’s magnitude. By proposing this alternative method of modeling extreme events, we add to the current body of literature, and the findings demonstrate its practical use for decision-making authorities—particularly financial traders who model high-volatility products like derivatives.

Cycle Fluctuations in the U.S. Real GDP and National Income and Product Accounts Aggregates

This article provides a new set of empirical regularities describing the U.S. macroeconomy, focusing on business cycle fluctuations in the real GDP and eleven major aggregates from the U.S. National Income and Product Accounts (NIPAs). Patterns of the cyclical fluctuations are assessed using filtering methodologies that adapt to the properties of the series being studied. We employ a recent dataset that includes the Great Recession caused by the 2008 financial crisis and the ensuing recovery. We aim to (1) examine the lead-lag relations via cross-correlations between the aggregate cycle in the U.S. real GDP and the cyclical movements in the eleven major NIPA aggregates; (2) investigate econometrically the inter-linkage between the cyclical component of real GDP and that of each NIPA aggregate by way of the Granger-causality test; and (3) evaluate the capability or the predictive power of each NIPA aggregate to forecast real GDP growth via three forecasting models. Comparisons are made with popular nonparametric HP and Baxter-King (BK) filters. The basic conclusion from the empirical analysis is that the adaptive model-based filters have demonstrated advantages over the commonly used HP and BK filters for business cycle analysis across very diverse economic series from the U.S. national accounts, and the structural time series model using smoothed trend and cycle estimates produced more accurate forecasts than the AR(p) model that forecasts directly using the unfiltered time series.

Trend inflation and exchange rate dynamics: A new Keynesian approach

This study examines the exchange rate implications of trend inflation within a two-country New Keynesian (NK) model. An NK Phillips curve generalized by trend inflation makes the inflation differential smoother, more persistent, and less sensitive to the real exchange rate. A Bayesian analysis with post-Bretton Woods data for Canada and the U.S. shows that the model's equilibrium, which relies on Taylor rules with a persistent trend inflation shock and strong policy inertia, mimics empirical regularities in exchange rates that are difficult to reconcile within a standard NK model. Trend inflation helps explain the empirical puzzles of the exchange rate dynamics.

Analysis of Detection of Empirical Regularity in Problems with a Similarity Operation Corresponding to Global Similarity

Analysis of Detection of Empirical Regularity in Problems with a Similarity Operation Corresponding to Global Similarity

An innovative approach for optimising CCP default management through agent-based modelling

This paper develops a rigorous model to analyse the market impact of liquidation. Invoking innovative techniques from agent-based simulation, we construct the order book's reaction function to liquidation. A methodology is then developed for establishing the optimal close-out strategy which balances the velocity of positional liquidation with that consequential market reaction function. This model can be used in parallel to more traditional calculations of market volatility to ensure that the overall risk capitalisation of a central clearing counterparty remains robust. In the case of financial markets, agent-based models often seek to account for the so-called stylised facts of financial markets. Stylised facts are simply empirical regularities that appear to be stable across markets and over time. Such facts range from statistical concepts, such as the distribution of returns, to more abstract notions such as stock market bubbles and crashes.

Compensation effect of mortality is a challenge to substantial lifespan extension of humans.

Despite frequent claims regarding radical extensions of human lifespan in the near future, many pragmatic scientists caution against excessive and baseless optimism on this front. In this study, we examine the compensation effect of mortality (CEM) as a potential challenge to substantial lifespan extension. The CEM is an empirical mortality regularity, often depicted as relative mortality convergence at advanced ages. Analysis of mortality data from 44 human populations, available in the Human Mortality Database, demonstrated that CEM can be represented as a continuous decline in relative mortality variation (assessed through the coefficient of variation and the standard deviation of the logarithm of mortality) with age, reaching a minimum corresponding to the species-specific lifespan. Through this method, the species-specific lifespan is determined to be 96-97years, closely aligning with estimates derived from correlations between Gompertz parameters (95-98years). Importantly, this representation of CEM can be achieved non-parametrically, eliminating the need for estimating Gompertz parameters. CEM is a challenge to lifespan extension, because it suggests that the true aging rate in humans (based on loss of vital elements, e.g., functional cells) remains stable at approximately 1% per year in the majority of human populations and is not affected by environmental or familial longevity factors. Given this rate of functional cell loss, one might anticipate that the total pool of functional cells could be entirely depleted by the age of 115-120years creating physiological limit to human lifespan. Mortality pattern of supercentenarians (110 + years) aligns with this prediction.

How does inflation propagate among CPI components? Evidence from the euro area

This study employs a time-varying parameter vector autoregressive (TVP-VAR) model to investigate infla- tion propagation and spillovers among twelve major Consumer Price Index (CPI) components across eleven euro area countries from 1999 to 2023. We uncover empirical regularities in the transmission channels of inflation, noting Transport and Clothing and Footwear as primary shock transmitters, whereas Communi- cation, Alcohol and Tobacco consistently absorb shocks. These insights, consistent across various contexts and countries, contribute to understanding inflation persistence and households’ inflation experiences in the Euro area.

Vertical Spillovers in Global Value Chains

This paper uses input-output relationships across highly disaggregated products to establish two empirical regularities with bilateral trade data. First, countries are likely to have revealed comparative advantage (RCA) in a product if they also have RCA in products that are upstream or downstream to that product. Second, the RCA of a product improves over time if the country experiences export demand shocks to its inputs or outputs. This suggests that being integrated as suppliers into the global production network can benefit countries by improving their capabilities across different stages of production.

Consequences of democratic backsliding in popular culture: evidence from blacklist in South Korea

ABSTRACT A burgeoning literature firmly establishes that democratic backsliding leaves negative imprints in various domains. However, this empirical regularity has not been extended to the realm of culture despite ample anecdotes pointing to the detrimental effect of democratic decays on the very backbone of cultural dynamism, the freedom of expression. To fill this lacuna, the article documents the case of deliberate infringement on freedom of expression in South Korea during its backsliding period (2008-2017). Using a difference-in-difference model on an original individual-level panel dataset, I report that the Blacklist project significantly damaged the careers of Korean movie workers, particularly those invisible from the public. The article suggests that the consequence of a backsliding government’s attempt to control public discourse can be surprisingly comprehensive because it instills self-censorship in the industry.

The English Sublexical Toolkit: Methods for indexing sound–spelling consistency

This work introduces the English Sublexical Toolkit, a suite of tools that utilizes an experience-dependent learning framework of sublexical knowledge to extract regularities from the English lexicon. The Toolkit quantifies the empirical regularity of sublexical units in both the reading and spelling directions (i.e., grapheme-to-phoneme and phoneme-to-grapheme) and at multiple grain sizes (i.e., phoneme/grapheme and onset/rime unit size). It can extract multiple experience-dependent regularity indices for words or pseudowords, including both frequency indices (e.g., grapheme frequency) and conditional probability indices (e.g., grapheme-to-phoneme probability). These tools provide (1) superior estimates of the regularities that better reflect the complexity of the sublexical system relative to previously published indices and (2) completely novel indices of sublexical units such as phonographeme frequency (i.e., combined units of individual phonemes and graphemes that are independent of processing direction). We demonstrate that measures from the toolkit explain significant amounts of variance in empirical data (naming of real words and lexical decision), and either outperform or are comparable to the best available consistency measures. The flexibility of the toolkit is further demonstrated by its ability to readily index the probability of different pseudowords pronunciations, and we report that the measures account for the majority of variance in these empirically observed probabilities. Overall, this work provides a framework and resources that can be flexibly used to identify optimal corpus-based consistency measures that help explain reading/spelling behaviors for real and pseudowords.

A Social Network Transmission Model of Investor Relations

ABSTRACT This study models a firm’s investors as connected via a social network and examines how an appropriate investor relations (IR) strategy can maximize information flow through this network. When IR can initially reach only a few investors, information flows faster when IR targets highly connected investors through, for example, direct contact. When IR can initially reach many investors, information flows faster from untargeted broadcast-type communications that reach random investors. Turning to empirically measurable outcomes of information flow, we show that the time series of bid-ask spreads have a hump-shaped pattern, first increasing and then decreasing. Faster information flows cause a sharper, but briefer, bid-ask spread spike. Such results provide a rigorous framework for thinking about how IR activities drive stock liquidity, and unite several observed empirical regularities into an investor social network-based framework for IR activities, a research area where descriptive empirical findings have outpaced theory.

Paving the way for sustainable environment in BRICS through technological innovation, sustainable energy, and financial development: heterogenous analyses

ABSTRACT The pervasive issue of global warming has propelled the continued empirical efforts by policymakers and research pundits geared towards finding sustainable solutions to salvaging the ecosystem. Consequently, this study evaluates the heterogenous impacts of technological innovation, sustainable energy, and financial development on environmental sustainability captured by CO2 emissions, methane emissions, and nitrous oxide emissions in the BRICS countries from 1995 to 2020. The study employs second-generation estimators comprising quantile regression (QR), augmented mean (AMG), common correlation effect group mean (CCEMG), and cross-sectional ARDL (CS-ARDL). The main findings show that among the indicators of technological innovation, high technology exports, ICT goods exports, and ICT services exports drive sustainable environment in the long run whereas environmental-related technology promotes both in the short run and long run. The moderating impacts of sustainable energy are evident through wind energy, solar energy, and hydrogen technology. Conversely, financial development measured by broad money and domestic credits to private sector hinders environmental sustainability. More so, the covariates entailing economic growth, population growth, poverty, and trade openness escalate the stock of pollutants. The empirical regularity of the main estimators is supported by outcomes of QR across the low, middle, and upper quantiles. On the policy front, the study recommends promoting initiatives that drive technology and renewable energy to enhance the sustainability of the BRICS’ environment.

Organization of production and income inequality

AbstractThis paper contributes to the literature that postulates a relationship between income inequality and the relative importance of “market” and “organization” in the direction of resources. The paper emphasizes that both are endogenous; therefore, the empirical associations observed in the empirical data between inequality measures and production organization variables cannot be interpreted as indicative of causal relationships. The paper solves for the composition and size of occupational groups, the distribution of firm size, and the distribution of income as market equilibrium outcomes of an occupational choice economy, and performs a comparative static analysis. We find that the interaction between cross‐economy differences in the distribution of general skills in the labor force and the loss of control in the supervision of workers by managers can explain the empirical regularities observed in the relationship between the organization of production (distribution of firm size) and income inequality (distribution of labor income). This explanation of the empirical regularities differs from others proposed in the literature, such as those based on institutional constraints or the market power of firms.

Corruption and Firm Growth: Evidence from around the World

Abstract We empirically investigate the relationship between corruption and growth using a firm-level dataset that is unique in scale, covering almost 88,000 firms across 141 economies in 2006–20, with wide-ranging corruption experiences. The scale and detail of our data allow us to explore the corruption-growth relationship at a very local level, within industries in a relatively narrow geography. We report three empirical regularities. First, firms that make zero informal payments tend to grow slower than bribers. Second, this result is driven by non-bribers in high-corruption countries. Third, among bribers, growth is decreasing in the amount of informal payments—in both high- and low-corruption countries. We suggest that this set of results may be reconciled with a simple model in which endogenously determined higher bribe rates lead to lower growth, while non-bribers are often excluded entirely from growth opportunities in high-corruption settings.

Facts about hospital-insurer contracting.

To use publicly available price transparency data files to establish empirical regularities about hospital-insurer contracting. Retrospective analysis of 10 price transparency data files from HCA Healthcare. Cross-sectional qualitative analysis of 524hospital-insurer contracts across 10 hospitals. We ascertain 4 empirical regularities in these files. First, hospitals contract with many payers, ranging from 35 to 82 across the hospitals in the sample. Second, contract structure varies significantly within and across hospitals: Of the 524 contracts in our sample, the median contract contained 9 contract elements, whereas the mean contract contained 1285 contract elements. Third, most of the contracts in our sample contained multiple contracting methodologies (eg, both fixed fee and percentage of charges). Fourth, these contracts indicated substantial variation for the same service within and across hospitals, validating findings from analyses based on claims data and hospital price transparency files. Hospital-insurer contracts dictate the flow and structure of a significant portion of total health care expenditure in the US. Increased attention by both researchers and policy makers would lead to a greater understanding of this vital-yet understudied-element of the market for hospital services.

On Rank r Empirical Regularities in the JSM Method of Automated Research Supporta

On Rank r Empirical Regularities in the JSM Method of Automated Research Supporta

Exploring Patterns of Human Mortality and Aging: A Reliability Theory Viewpoint.

The most important manifestation of aging is an increased risk of death with advancing age, a mortality pattern characterized by empirical regularities known as mortality laws. We highlight three significant ones: the Gompertz law, compensation effect of mortality (CEM), and late-life mortality deceleration and describe new developments in this area. It is predicted that CEM should result in declining relative variability of mortality at older ages. The quiescent phase hypothesis of negligible actuarial aging at younger adult ages is tested and refuted by analyzing mortality of the most recent birth cohorts. To comprehend the aging mechanisms, it is crucial to explain the observed empirical mortality patterns. As an illustrative example of data-directed modeling and the insights it provides, we briefly describe two different reliability models applied to human mortality patterns. The explanation of aging using a reliability theory approach aligns with evolutionary theories of aging, including idea of chronic phenoptosis. This alignment stems from their focus on elucidating the process of organismal deterioration itself, rather than addressing the reasons why organisms are not designed for perpetual existence. This article is a part of a special issue of the journal that commemorates the legacy of the eminent Russian scientist Vladimir Petrovich Skulachev (1935-2023) and his bold ideas about evolution of biological aging and phenoptosis.