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Articles 91 - 120 of 3476
Full-Text Articles in Economics
Data-Driven Mechanism Design: Jointly Eliciting Preferences And Information, Dirk Bergemann, Marek Bojko, Paul Dutting, Renato Paes Leme, Haifeng Xu, Song Zuo
Data-Driven Mechanism Design: Jointly Eliciting Preferences And Information, Dirk Bergemann, Marek Bojko, Paul Dutting, Renato Paes Leme, Haifeng Xu, Song Zuo
Cowles Foundation Discussion Papers
We study mechanism design in environments where agents have private preferences and private information about a common payoff-relevant state. In such settings with multi-dimensional types, standard mechanisms fail to implement efficient allocations. We address this limitation by proposing data-driven mechanisms that condition transfers on additional post-allocation information, modeled as an estimator of the payoff-relevant state. Our mechanisms extend the classic Vickrey–Clarke–Groves framework. We show they achieve exact implementation in posterior equilibrium when the state is fully revealed or utilities are affine in an unbiased estimator. With a consistent estimator, they achieve approximate implementation that converges to exact implementation as the …
Multidimensional Sorting: Comparative Statics, Joe Boerma, Andrea Ottolini, Aleh Tsyvinski
Multidimensional Sorting: Comparative Statics, Joe Boerma, Andrea Ottolini, Aleh Tsyvinski
Cowles Foundation Discussion Papers
In sorting literature, comparative statics for multidimensional assignment models with general output functions and input distributions is an important open question. We provide a complete theory of comparative statics for technological change in general multidimensional assignment models. Our main result is that any technological change is uniquely decomposed into two distinct components. The first component (gradient) gives a characterization of changes in marginal earnings through a Poisson equation. The second component (divergence-free) gives a characterization of labor reallocation. For U.S. data, we quantify equilibrium responses in sorting and earnings with respect to cognitive skill-biased technological change.
Drivers Of Racial Differences In C-Sections, Adriana Corredor-Waldron, Janet Currie, Molly Schnell
Drivers Of Racial Differences In C-Sections, Adriana Corredor-Waldron, Janet Currie, Molly Schnell
Cowles Foundation Discussion Papers
Black mothers with a trial of labor are 25 percent more likely to deliver by C-section than non-Hispanic White mothers. The gap is largest among mothers with the lowest risk and is reduced by only one-fifth when controlling for observed medical risk factors, sociodemographic characteristics, hospital, and physician or medical practice group. Remarkably, the gap disappears when performing a C-section is more costly due to a concurrent pre-labor C-section limiting surgical resources. This finding is consistent with provider discretion—rather than differences in unobserved medical risk—accounting for persistent racial disparities in delivery method. The additional intrapartum C-sections that occur among low-risk …
Information Without Rents: Mechanism Design Without Expected Utility, Ernesto Rivera Mora, Philipp Strack
Information Without Rents: Mechanism Design Without Expected Utility, Ernesto Rivera Mora, Philipp Strack
Cowles Foundation Discussion Papers
We study mechanism design for a sophisticated agent with non-expected utility (EU) preferences. We show that the revelation principle holds if and only if all types are EU maximizers: if at least one type is a non-EU maximizer, randomizing over dynamic mechanisms generates a strictly larger set of implementable allocations than using static mechanisms. Moreover, dynamic stochastic mechanisms can fully extract the private information of any type who doesn’t have uniformly quasi-concave preferences without providing that type any rent. Full-surplus extraction is possible in a broad variety of non-EU environments, but impossible for types with concave preferences.
Regulating Privacy Policies On Digital Platforms, Michele Bisceglia, Alessandro Bonatti, Fiona Scott Morton
Regulating Privacy Policies On Digital Platforms, Michele Bisceglia, Alessandro Bonatti, Fiona Scott Morton
Cowles Foundation Discussion Papers
We study how privacy regulation affects menu pricing by a monopolist platform that collects and monetizes personal data. Consumers differ in privacy valuation and sophistication: naive users ignore privacy losses, while sophisticated users internalize them. The platform designs prices and data collection options to screen users. Without regulation, privacy allocations are distorted and naive users are exploited. Regulation through privacy-protecting defaults can create a market for information by inducing payments for data; hard caps on data collection protect naive users but may restrict efficient data trade.
Probability Pricing, Eduardo Dávila, Cecilia Parlatore, Ansgar Walther
Probability Pricing, Eduardo Dávila, Cecilia Parlatore, Ansgar Walther
Cowles Foundation Discussion Papers
This paper develops probability pricing, extending cash flow pricing to quantify the willingnessto-pay for changes in probabilities. We show that the value of any marginal change in probabilities can be expressed as a standard asset-pricing formula with hypothetical cash flows derived from changes in the survival function. This equivalence between probability and cash flow valuation allows us to construct hedging strategies and systematically decompose individual and aggregate willingness-to-pay. Four applications examine the valuation of changes in the distribution of aggregate consumption, the efficiency effects of varying performance precision in principal-agent problems, and the welfare implications of public and private information.
Marriage, Labor Supply And The Dynamics Of The Social Safety Net, Hamish Low, Costas Meghir, Luigi Pistaferri, Alessandra Voena
Marriage, Labor Supply And The Dynamics Of The Social Safety Net, Hamish Low, Costas Meghir, Luigi Pistaferri, Alessandra Voena
Cowles Foundation Discussion Papers
The 1996 US welfare reform introduced time limits on welfare receipt. We use quasi-experimental evidence and a rich life-cycle model to understand the impact of time limits on different margins of behavior and well-being. We stress the impact of marital status and marital transitions on mitigating the cost and impact of time limits. Time limits cause women to defer claiming in anticipation of future needs and to work more, effects that depend on the probabilities of marriage and divorce. They also cause an increase in employment among single mothers and reduce divorce, but their introduction costs women 0.7% of lifetime …
Relu-Based And Dnn-Based Generalized Maximum Score Estimators, Xiaohong Chen, Wayne Yuan Gao, Likand Wen
Relu-Based And Dnn-Based Generalized Maximum Score Estimators, Xiaohong Chen, Wayne Yuan Gao, Likand Wen
Cowles Foundation Discussion Papers
We propose a new formulation of the maximum score estimator that uses compositions of rectified linear unit (ReLU) functions, instead of indicator functions as in Manski (1975, 1985), to encode the sign alignment restrictions. Since the ReLU function is Lipschitz, our new ReLU-based maximum score criterion function is substantially easier to optimize using standard gradient-based optimization pacakges. We also show that our ReLU-based maximum score (RMS) estimator can be generalized to an umbrella framework defined by multi-index single-crossing (MISC) conditions, while the original maximum score estimator cannot be applied. We establish the n −s/(2s+1) convergence rate and asymptotic normality for …
New Measures For Richer Theories: Some Thoughts And An Example, Orazio Attanasio, Victor Sancibrian, Federica Ambrosio
New Measures For Richer Theories: Some Thoughts And An Example, Orazio Attanasio, Victor Sancibrian, Federica Ambrosio
Cowles Foundation Discussion Papers
For a long time, the majority of economists doing empirical work relied on choice data, while data based on answers to hypothetical questions, stated preferences or measures of subjective beliefs were met with some skepticism. Although this has changed recently, much work needs to be done. In this paper, we emphasize the identifying content of new economic measures. In the first part of the paper, we discuss where the literature on measures in economics stands at the moment. We first consider how the design and use of new measures can help identify causal links and structural parameters under weaker assumptions …
Optimization Via Strategic Law Of Large Numbers, Xiaohong Chen, Zengjing Chen, Wayne Yuan Gao, Xiaodong Yan, Guodong Zhang
Optimization Via Strategic Law Of Large Numbers, Xiaohong Chen, Zengjing Chen, Wayne Yuan Gao, Xiaodong Yan, Guodong Zhang
Cowles Foundation Discussion Papers
This paper proposes a novel framework for the global optimization of a continuous function in a bounded rectangular domain. Specifically, we show that: (1) global optimization is equivalent to optimal strategy formation in a two-armed decision problem with known distributions, based on the Strategic Law of Large Numbers we establish; and (2) a sign-based strategy based on the solution of a parabolic PDE is asymptotically optimal. Motivated by this result, we propose a class of Strategic Monte Carlo Optimization (SMCO) algorithms, which uses a simple strategy that makes coordinate-wise two-armed decisions based on the signs of …
Worker Rights In Collective Bargaining, Benjamin W. Arold, Elliott Ash, W. Bentley Macleod, Suresh Naidu
Worker Rights In Collective Bargaining, Benjamin W. Arold, Elliott Ash, W. Bentley Macleod, Suresh Naidu
Cowles Foundation Discussion Papers
Collective bargaining agreements (CBAs) specify the contractual rights of unionized workers, but their full legal content has not yet been analyzed by economists. This paper develops novel natural language methods to analyze the empirical determinants and economic value of these rights using a new collection of 30,000 CBAs from Canada in the period 1986-2015. We parse legally binding rights (e.g., “workers shall receive. . . ”) and obligations (e.g., “the employer shall provide. . . ”) from contract text, and validate our measures through evaluation of clause pairs and comparison to firm surveys on HR practices. Using timevarying province-level variation …
Slim: Stochastic Learning And Inference In Overidentified Models, Xiaohong Chen, Min Seong Kim, Sokbae Lee, Myung Hwan Seo, Myunghyun Song
Slim: Stochastic Learning And Inference In Overidentified Models, Xiaohong Chen, Min Seong Kim, Sokbae Lee, Myung Hwan Seo, Myunghyun Song
Cowles Foundation Discussion Papers
We propose SLIM (Stochastic Learning and Inference in overidentified Models), a scalable stochastic approximation framework for nonlinear GMM. SLIM forms iterative updates from independent mini-batches of moments and their derivatives, producing unbiased directions that ensure almost-sure convergence. It requires neither a consistent initial estimator nor global convexity and accommodates both fixed-sample and random-sampling asymptotics. We further develop an optional second-order refinement and inference procedures based on random scaling and plug-in methods, including plug-in, debiased plug-in, and online versions of the Sargan–Hansen J-test tailored to stochastic learning. In Monte Carlo experiments based on a nonlinear EASI demand system with 576 moment …
Local Overidentification And Efficiency Gains In Modern Causal Inference And Data Combination, Xiaohong Chen, Haitian Xie
Local Overidentification And Efficiency Gains In Modern Causal Inference And Data Combination, Xiaohong Chen, Haitian Xie
Cowles Foundation Discussion Papers
This paper studies nonparametric local (over-)identification, in the sense of Chen and Santos (2018), and the associated semiparametric efficiency in modern causal frameworks. We develop a unified approach that begins by translating structural models with latent variables into their induced statistical models of observables and then analyzes local overidentification through conditional moment restrictions. We apply this approach to three leading models: (i) the general treatment model under unconfoundedness, (ii) the negative control model, and (iii) the long-term causal inference model under unobserved confounding. The first design yields a locally just-identified statistical model, implying that all regular asymptotically linear estimators of …
Climate Shocks And State Formation: The 1970 Bhola Cyclone And The Birth Of Bangladesh, Sultan Mehmood, Ahmed Mushfiq Mobarak
Climate Shocks And State Formation: The 1970 Bhola Cyclone And The Birth Of Bangladesh, Sultan Mehmood, Ahmed Mushfiq Mobarak
Discussion Papers
State formation through secession often requires two critical steps: building mass support for independence, and engaging in violent conflict against a state resisting territorial loss. Combining satellite data with archival sources, we statistically document how exposure to the 1970 Bhola cyclone in East Pakistan which killed 350,000 people led to a rise in separatist sentiments expressed in voting booths, and later induced citizens to take up arms against the government and engage in guerrilla warfare. We identify the cyclone as a focal point that helped galvanize dispersed separatist sentiments into an organized political movement and war, in part by revealing …
Safely Exploring Novel Actions In Recommender Systems Via Deployment-Efficient Policy Learning, Haruka Kiyohara, Yusuke Narita, Yuta Saito, Kei Tateno, Takuma Udagawa
Safely Exploring Novel Actions In Recommender Systems Via Deployment-Efficient Policy Learning, Haruka Kiyohara, Yusuke Narita, Yuta Saito, Kei Tateno, Takuma Udagawa
Cowles Foundation Discussion Papers
In many real recommender systems, novel items are added frequently over time. The importance of sufficiently presenting novel actions has widely been acknowledged for improving long-term user engagement. A recent work builds on Off-Policy Learning (OPL), which trains a policy from only logged data, however, the existing methods can be unsafe in the presence of novel actions. Our goal is to develop a framework to enforce exploration of novel actions with a guarantee for safety. To this end, we first develop Safe Off-Policy Policy Gradient (Safe OPG), which is a model-free safe OPL method based on a high confidence off-policy …
Disclosure And The Pace Of Drug Development, Colleen Cunnningham, Florian Ederer, Charles Hodgson, Zhichun Wang
Disclosure And The Pace Of Drug Development, Colleen Cunnningham, Florian Ederer, Charles Hodgson, Zhichun Wang
Cowles Foundation Discussion Papers
Policies that mandate disclosure of innovative project outcomes aim to increase innovation by limiting wasteful duplicative innovation. Yet, such policies change not only the ex-post information environment but also firms' ex-ante innovation incentives. Firms may slow down their own innovation efforts in anticipation of increased disclosure by others. We examine the innovation-related impacts of the 2017 FDA Final Rule amendment, which mandates disclosure of clinical trial results for pharmaceutical firms. We show that the policy hastened and increased disclosure of results for clinical trials post-completion, but also increased the time to completion of clinical trials, the time between early phases …
Edgeworth Expansions In Curved Cross Section Autoregression, Peter C.B. Phillips
Edgeworth Expansions In Curved Cross Section Autoregression, Peter C.B. Phillips
Cowles Foundation Discussion Papers
Edgeworth expansions are developed for the finite sample distribution of the least squares estimator in a time series parametric first order autoregression with Hilbert space curves of cross section data. The main result extends to this functional data environment the Edgeworth expansion in the corresponding scalar time series AR(1). In doing so, the results show how function-valued cross section data, and hence general forms of cross section dependence, affect the finite sample distribution of the serial correlation coefficient. Autoregressions with functional fixed effect intercepts are included and the results therefore relate to dynamic panel autoregression with individual effects. The primary …
What Can Trends In Emergency Department Visits Tell Us About Child Mental Health?, Han Choi, Adriana Corredor-Waldron, Janet Currie, Chris Felton
What Can Trends In Emergency Department Visits Tell Us About Child Mental Health?, Han Choi, Adriana Corredor-Waldron, Janet Currie, Chris Felton
Cowles Foundation Discussion Papers
Increases in mental health diagnoses and suicidal behaviors in Emergency Departments are often cited as evidence of an accelerating child mental health crisis. We ask whether trends in ED visits provide an accurate picture of changes in U.S. child mental health. These measures have been profoundly affected by changing conventions about screening, defining, and coding of mental illness. We conclude that child mental health has been deteriorating, but not by the startling magnitudes suggested by jumps and trends in some measures such as suicidal ideation. Although reported suicidal behaviors rose 228% from 2006–2021, the true rise in mental health disorders …
Optimal Estimation In A Multicointegrated System, Igor Kheifets, Peter C.B. Phillips
Optimal Estimation In A Multicointegrated System, Igor Kheifets, Peter C.B. Phillips
Cowles Foundation Discussion Papers
Optimal estimation is explored in long run relations that are modeled within a semiparametric triangular multicointegrated system. In nonsingular cointegrated systems, where there is no multicointegration, optimal estimation is well understood (Phillips, 1991a). This paper establishes corresponding optimal results for singular systems, thereby accommodating a wide class of multicointegrated nonstationary time series with nonparametric transient dynamics. The optimality and sub-optimality of existing estimators are considered and new optimal estimators of both the cointegrating and multicointegrating coefficients are introduced that are based on spectral regression.
The Changing Nature Of International Trade And Its Implications For Development, Pinelopi Goldberg, Michele Ruta
The Changing Nature Of International Trade And Its Implications For Development, Pinelopi Goldberg, Michele Ruta
Discussion Papers
This paper revisits the relationship between international trade, trade policy, and development in light of the structural, policy, and geopolitical shifts that have transformed globalization over the past decade. While trade has historically supported development through both static and dynamic channels, we argue that the latter—those inducing structural transformation and institutional change—have been far more consequential for long-run development. Through access to global markets, participation in global value chains, and knowledge and technology transfers, and by providing an anchor for reform, trade and trade agreements have contributed to productivity gains, technological progress, quality and skill upgrading, and institutional change in …
The Changing Nature Of International Trade And Its Implications For Development, Pinelopi Goldberg, Michele Ruta
The Changing Nature Of International Trade And Its Implications For Development, Pinelopi Goldberg, Michele Ruta
Cowles Foundation Discussion Papers
This chapter revisits the relationship between international trade, trade policy, and development in light of the structural, policy, and geopolitical shifts that have transformed globalization over the past decade. While trade has historically supported development through both static and dynamic channels, we argue that the latter—those inducing structural transformation and institutional change—have been far more consequential for long-run development. Through access to global markets, participation in global value chains, and knowledge and technology transfers, and by providing an anchor for reform, trade and trade agreements have contributed to productivity gains, technological progress, quality and skill upgrading, and institutional change in …
Large-Scale Curve Time Series With Common Stochastic Trends, Degui Li, Yuning Li, Peter C. B. Phillips
Large-Scale Curve Time Series With Common Stochastic Trends, Degui Li, Yuning Li, Peter C. B. Phillips
Cowles Foundation Discussion Papers
This paper studies high-dimensional curve time series with common stochastic trends. A dual functional factor model structure is adopted with a high-dimensional factor model for the observed curve time series and a low-dimensional factor model for the latent curves with common trends. A functional PCA technique is applied to estimate the common stochastic trends and functional factor loadings. Under some regularity conditions we derive the mean square convergence and limit distribution theory for the developed estimates, allowing the dimension and sample size to jointly diverge to infinity. We propose an easy-to-implement criterion to consistently select the number of common stochastic …
Growth With Firm-To-Firm Trade, Samuel Kortum, Bernardo Ribeiro
Growth With Firm-To-Firm Trade, Samuel Kortum, Bernardo Ribeiro
Cowles Foundation Discussion Papers
We explore how connections between buyers and suppliers of intermediate inputs evolve over time to promote firm growth. To formalize this process we develop a dynamic model of a granular endogenous production network, making stark assumptions that yield a tractable parsimonious framework. In the model, producers gradually build up a network of contacts by meeting other producers and source an intermediate input from their cheapest contact at any moment. They retain full recall, so can always switch to a producer contacted previously, even if they never bought from it before. Through this process the production network itself becomes an endogenous …
Pipeline Vs. Choice: The Global Gender Gap In Stem Applications, Isaac Ahimbisibwe, Adam Altjmed, Georgy Artemov, Andres Barrios-Fernandez, Aspasia Bizopoulou, Martti Kaila, Jin-Tan Liu, Rigissa Megalokonomou, José Montalban, Christopher Neilson, Jintao Sun, Sebastian Otero, Xiaoyang Ye
Pipeline Vs. Choice: The Global Gender Gap In Stem Applications, Isaac Ahimbisibwe, Adam Altjmed, Georgy Artemov, Andres Barrios-Fernandez, Aspasia Bizopoulou, Martti Kaila, Jin-Tan Liu, Rigissa Megalokonomou, José Montalban, Christopher Neilson, Jintao Sun, Sebastian Otero, Xiaoyang Ye
Cowles Foundation Discussion Papers
Women account for only 35% of global STEM graduates, a share unchanged for a decade. We use administrative microdata from centralized university admissions in ten systems to deliver the first crossnational decomposition of the STEM gender gap into a pipeline gap (academic preparedness) and a choice gap (first-choice field conditional on eligibility). In deferred-acceptance platforms where eligibility is score-based, we isolate preferences from access. The pipeline gap varies widely, from -19 to +31 percentage points across education systems. By contrast, the choice gap is remarkably stable: high-scoring women are 25 percentage points less likely than men to rank STEM first.
Multidimensional Monotonicity And Economic Applications, Frank Yang, Kai Hao Yang
Multidimensional Monotonicity And Economic Applications, Frank Yang, Kai Hao Yang
Cowles Foundation Discussion Papers
We characterize the extreme points of multidimensional monotone functions from [0,1]n to [0,1], as well as the extreme points of the set of one-dimensional marginals of these functions. These characterizations lead to new results in various mechanism design and information design problems, including public good provision with interdependent values; interim efficient bilateral trade mechanisms; asymmetric reduced form auctions; and optimal private private information structure. As another application, we also present a mechanism anti-equivalence theorem for two-agent, two-alternative social choice problems: A mechanism is payoff-equivalent to a deterministic DIC mechanism if and only if they are ex-post equivalent.
Tariffs And Trade Deficits, Lorenzo Caliendo, Samuel Kortum, Fernando Parro
Tariffs And Trade Deficits, Lorenzo Caliendo, Samuel Kortum, Fernando Parro
Cowles Foundation Discussion Papers
We develop a dynamic multi-country Ricardian trade model with aggregate uncertainty, where trade imbalances emerge as countries exchange goods and assets. We introduce a method for computing counterfactuals in this setting, which doesn't require specifying the stochastic process of shocks or solving for asset prices. Applying the model to tariff shocks, we quantify their effects on prices, income, spending, and trade imbalances. We find that higher U.S. tariffs reduce the U.S. trade deficit through general equilibrium adjustments, but raise domestic prices and lower real consumption. Our findings highlight that movements in trade imbalances are shaped by the structure of global …
The Effect Of Education Policy On Crime: An Intergenerational Perspective, Ulrika Ahrsjö, Costas Meghir, Mårten Palme, Marieke Schnabel
The Effect Of Education Policy On Crime: An Intergenerational Perspective, Ulrika Ahrsjö, Costas Meghir, Mårten Palme, Marieke Schnabel
Cowles Foundation Discussion Papers
We examine the intergenerational effect of education policy on crime. Using administrative data that links outcomes across generations with crime records, we show that the Swedish comprehensive school reform, gradually implemented between 1949 and 1962, reduced conviction rates for both the generation directly affected by the reform and their sons. The reduction in conviction rates occurred in several types of crime. Mediation analysis suggests that key channels include increased parental educational attainment and household income, as well as reduced criminal behavior among fathers.
Decomposing Trends In The Gender Gap For Highly Educated Workers, Joseph G. Altonji, John Eric Humphries, Yagmur Yuksel, Ling Zhong
Decomposing Trends In The Gender Gap For Highly Educated Workers, Joseph G. Altonji, John Eric Humphries, Yagmur Yuksel, Ling Zhong
Cowles Foundation Discussion Papers
This paper examines the gender gap in log earnings among full-time, college-educated workers born between 1931 and 1984. Using data from the National Survey of College Graduates and other sources, we decompose the gender earnings gap across birth cohorts into three components: (i) gender differences in the relative returns to undergraduate and graduate fields, (ii) gender-specific trends in undergraduate field, graduate degree attainment, and graduate field, and (iii) a cohortspecific “residual component” that shifts the gender gap uniformly across all college graduates. We have three main findings. First, when holding the relative returns to fields constant, changes in fields of …
Offline Contextual Bandits In The Presence Of New Actions, Ren Kishimoto, Tatsuhiro Shimizu, Kazuki Kawamura, Takanori Muroi, Yusuke Narita, Yuki Sasamoto, Kei Tateno, Takuma Udagawa, Yuta Saito
Offline Contextual Bandits In The Presence Of New Actions, Ren Kishimoto, Tatsuhiro Shimizu, Kazuki Kawamura, Takanori Muroi, Yusuke Narita, Yuki Sasamoto, Kei Tateno, Takuma Udagawa, Yuta Saito
Cowles Foundation Discussion Papers
Automated decision-making algorithms drive applications in domains such as recommendation systems and search engines. These algorithms often rely on off-policy contextual bandits or off-policy learning (OPL). Conventionally, OPL selects actions that maximize the expected reward within an existing action set. However, in many real-world scenarios, actions—such as news articles or video content—change continuously, and the action space evolves over time compared to when the logged data was collected. We define actions introduced after deploying the logging policy as new actions and focus on the problem of OPL with new actions. Existing OPL methods cannot learn and select new actions because …
Order Statistics As Finite Mixtures, José-Antonio Espín-Sánchez, Charles Hodgson, Kevin O’Neill
Order Statistics As Finite Mixtures, José-Antonio Espín-Sánchez, Charles Hodgson, Kevin O’Neill
Cowles Foundation Discussion Papers
We propose a new way to obtain identification results using order statistics as finite mixtures with two key properties: i) the weights are known integer numbers; and ii) the elements of the mixture are the distributions of the maximum over a subset of the original random variables. We leverage Exponentiated Distributions (ED), which extend extreme value theory results. ED are max-stable, and we show that finite mixtures of ED are linearly independent. This enables us to derive non-parametric identification results and extend commonly known results using Gumbel and Fréchet distributions, both examples of ED. The results have broad applications in …