Showing papers by "Instituto Tecnológico Autónomo de México published in 2021"

Why Working from Home Will Stick

Abstract: COVID-19 drove a mass social experiment in working from home (WFH). We survey more than 30,000 Americans over multiple waves to investigate whether WFH will stick, and why. Our data say that 20 percent of full workdays will be supplied from home after the pandemic ends, compared with just 5 percent before. We develop evidence on five reasons for this large shift: better-than-expected WFH experiences, new investments in physical and human capital that enable WFH, greatly diminished stigma associated with WFH, lingering concerns about crowds and contagion risks, and a pandemic-driven surge in technological innovations that support WFH. We also use our survey data to project three consequences: First, employees will enjoy large benefits from greater remote work, especially those with higher earnings. Second, the shift to WFH will directly reduce spending in major city centers by at least 5-10 percent relative to the pre-pandemic situation. Third, our data on employer plans and the relative productivity of WFH imply a 5 percent productivity boost in the post-pandemic economy due to re-optimized working arrangements. Only one-fifth of this productivity gain will show up in conventional productivity measures, because they do not capture the time savings from less commuting.

New Results on Parameter Estimation via Dynamic Regressor Extension and Mixing: Continuous and Discrete-Time Cases

Abstract: We present some new results on the dynamic regressor extension and mixing parameter estimators for linear regression models recently proposed in the literature. This technique has proven instrumental in the solution of several open problems in system identification and adaptive control. The new results include the following, first, a unified treatment of the continuous and the discrete-time cases; second, the proposal of two new extended regressor matrices, one which guarantees a quantifiable transient performance improvement , and the other exponential convergence under conditions that are strictly weaker than regressor persistence of excitation; and, third, an alternative estimator ensuring convergence in finite-time whose adaptation gain, in contrast with the existing one, does not converge to zero. Simulations that illustrate our results are also presented.

COVID-19 Is a Persistent Reallocation Shock

Abstract: Drawing on data from the firm-level Survey of Business Uncertainty, we present three pieces of evidence that COVID-19 is a persistent reallocation shock. First, rates of excess job and sales reallocation over 24-month periods (looking back 12 months and ahead 12 months) have risen sharply since the pandemic struck, especially for sales. Second, as of December 2020, firm-level forecasts of sales revenue growth over the next year imply a continuation of recent changes, not a reversal. Third, COVID-19 shifted relative employment growth trends in favor of industries with a high capacity for employees to work from home.

Modeling law search as prediction

Abstract: Law search is fundamental to legal reasoning and its articulation is an important challenge and open problem in the ongoing efforts to investigate legal reasoning as a formal process. This Article formulates a mathematical model that frames the behavioral and cognitive framework of law search as a sequential decision process. The model has two components: first, a model of the legal corpus as a search space and second, a model of the search process (or search strategy) that is compatible with that environment. The search space has the structure of a “multi-network”—an interleaved structure of distinct networks—developed in earlier work. In this Article, we develop and formally describe three related models of the search process. We then implement these models on a subset of the corpus of U.S. Supreme Court opinions and assess their performance against two benchmark prediction tasks. The first is to predict the citations in a document from its semantic content. The second is to predict the search results generated by human users. For both benchmarks, all search models outperform a null model with the learning-based model outperforming the other approaches. Our results indicate that through additional work and refinement, there may be the potential for machine law search to achieve human or near-human levels of performance.

Let's (not) get together! The role of social norms on social distancing during COVID-19.

Abstract: While effective preventive measures against COVID-19 are now widely known, many individuals fail to adopt them. This article provides experimental evidence about one potentially important driver of compliance with social distancing: social norms. We asked each of 23,000 survey respondents in Mexico to predict how a fictional person would behave when faced with the choice about whether or not to attend a friend's birthday gathering. Every respondent was randomly assigned to one of four social norms conditions. Expecting that other people would attend the gathering and/or believing that other people approved of attending the gathering both increased the predicted probability that the fictional character would attend the gathering by 25%, in comparison with a scenario where other people were not expected to attend nor to approve of attending. Our results speak to the potential effects of communication campaigns and media coverage of compliance with, and normative views about, COVID-19 preventive measures. They also suggest that policies aimed at modifying social norms or making existing ones salient could impact compliance.

Calibration and Uncertainty Quantification of Convective Parameters in an Idealized GCM

Abstract: Parameters in climate models are usually calibrated manually, exploiting only small subsets of the available data. This precludes an optimal calibration and quantification of uncertainties. Traditi...

Job Creation and Investment in Imperfect Capital and Labor Markets

Abstract: This paper aims to weigh the restrictions to job creation imposed by labor market imperfections with respect to financial market imperfections The authors want to see which restriction is more severe, and thus assess which is more powerful in creating permanent employment if it were removed,A structural estimation is performed The policy rules of the dynamic programming model are integrated into a simulated maximum likelihood procedure by which the model parameters are recovered Data come from the CBBE (Balance Sheet data from the Bank of Spain) Identification of key parameters comes mainly from the observation of debt variation and sluggish adjustment to permanent labor,Long-run permanent employment increases up to 69% when financial constraints are removed, whereas permanent employment only increases up to 54% when employment protection or firing costs are eliminated The main finding of this paper is that the long-run expansion of permanent employment is larger when financial imperfections are removed than when firing costs are removed, even when there are important wage increases that moderate these employment expansions,The removal of firing costs has been suggested by several economists as a result of the analysis of labor market imperfections These policies, however, face the strong opposition of labor unions This paper shows that the goals of permanent job creation can be accomplished without removing employment protection but by means of enhancing financial access to firms,The connection between financial constraints and employment has been studied in recent years, motivated by the Great Recession However, there is no assessment of how financial and labor market imperfections compare with each other to restrict permanent job creation This comparison is crucial for policy analysis This study is an attempt to fill out this gap in the economic literature No previous research has attempted to perform this very important comparison

Virtual charismatic leadership and signaling theory: A prospective meta-analysis in five countries

Abstract: Drawing upon signaling theory, charismatic leadership tactics (CLTs) have been identified as a trainable set of skills. Although organizations rely on technology-mediated communication, the effects of CLTs have not been examined in a virtual context. Preregistered experiments were conducted in face-to-face (Study 1; n = 121) and virtual settings (Study 2; n = 128) in the United States. In Study 3, we conducted virtual replications in Austria (n = 134), France (n = 137), India (n = 128), and Mexico (n = 124). Combined with past experiments, the meta-analytic effect of CLTs on performance (Cohen’s d = 0.52 in-person, k = 4; Cohen’s d = 0.21 overall, k = 10) and engagement in an extra-role task (Cohen’s d = 0.19 overall; k = 6) indicate large to moderate effects. Yet, for performance in a virtual context Cohen’s d ranged from −0.25 to 0.17 (Cohen’s d = 0.01 overall; k = 6). Study 4 (n = 129) provided mixed support for signaling theory in a virtual context, linking CLTs to some positive evaluations. We conclude with guidance for future research on charismatic leadership and signaling theory.

Identification of Fuzzy Rule-Based Models With Collaborative Fuzzy Clustering.

Abstract: Fuzzy rule-based models (FRBMs) are sound constructs to describe complex systems. However, in reality, we may encounter situations, where the user or owner of a system only owns either the input or output data of that system (the other part could be owned by another user); and due to the consideration of data privacy, he/she could not obtain all the needed data to build the FRBMs. Since this type of situation has not been fully realized (noticed) and studied before, our objective is to come up with some strategy to address this challenge to meet the specific privacy consideration during the modeling process. In this study, the concept and algorithm of the collaborative fuzzy clustering (CFC) are applied to the identification of FRBMs, describing either multiple-input-single-output (MISO) or multiple-input-multiple-output (MIMO) systems. The collaboration between input and output spaces based on their structural information (conveyed in terms of the corresponding partition matrices) makes it possible to build FRBMs when input and output data could not be collected and used in unison. Surprisingly, on top of this primary pursuit, with the collaboration mechanism the input and output spaces of a system are endowed with an innovative way to comprehensively share, exchange, and utilize the structural information between each other, which results in their more relevant structures that guarantee better model performance compared with performance produced by some state-of-the-art modeling strategies. The effectiveness of the proposed approach is demonstrated by experiments on a series of synthetic and publicly available datasets.

When is job control most useful for idea championing? Role conflict and psychological contract violation effects

Abstract: Drawing from conservation of resources theory, this article investigates the relationship between job control (a critical job resource) and idea championing, as well as how this relationship may be augmented by stressful work conditions that can lead to resource losses, such as conflicting work role demands and psychological contract violations. With quantitative data collected from employees of an organization that operates in the chemical sector, this study reveals that job control increases the propensity to champion innovative ideas. This effect is especially salient when employees experience high levels of role conflict and psychological contract violations. For organizations, the results demonstrate that giving employees more control over whether they invest in championing activities will be most beneficial when those employees also face resource-draining work conditions, in the form of either incompatible role expectations or unfilled employer obligations.

Let Me Work From Home, or I Will Find Another Job

Abstract: Four in ten Americans who currently work from home at least one day a week would seek another job if employers require a full return to business premises. In addition, most employees would look favorably on a new job that offers the same pay and the option to work from home 2 or 3 days a week. These employee attitudes are pushing many employers to permanently alter working arrangements. As of June 2021, employers plan for their employees to spend 1.2 full days per week working from home after the pandemic ends. These planned levels of post-pandemic working from home have risen 23% in the past year. Our survey-based evidence also suggests that high rates of quits and job openings in recent months partly reflect a re-sorting of workers with respect to a newly salient job attribute – namely, the scope for remote work.

Investment and operational decisions for start-up companies: a game theory and Markov decision process approach

Abstract: This paper analyses the contract between an entrepreneur and an investor, using a non-zero sum game in which the entrepreneur is interested in company survival and the investor in maximizing expected net present value. Theoretical results are given and the model’s usefulness is exemplified using simulations. We have observed that both the entrepreneur and the investor are better off under a contract which involves repayments and a share of the start-up company. We also have observed that the entrepreneur will choose riskier actions as the repayments become harder to meet up to a level where the company is no longer able to survive.

A PI+passivity-based control of a wind energy conversion system enabled with a solid-state transformer

Abstract: In this paper, we propose a new control scheme for a wind energy conversion system connected to a solid-state transformer-enabled distribution microgrid. The system consists of a wind turbine, a pe...

The machinery of #techno-colonialism crafting “democracy.” A glimpse into digital sub-netizenship in Mexico

Abstract: This article elaborates the concepts of techno-colonialism and sub-netizenship to explore the renewal of colonial processes through the digitalization of “democracy.” Techno-colonialism is conceive...

Illegal drug market responses to state recreational cannabis laws

Abstract: Background and aims In the United States, 15 states and the District of Columbia have implemented recreational cannabis laws (RCLs) legalizing recreational cannabis use. We aimed to estimate the association between RCLs and street prices, potency, quality and law enforcement seizures of illegal cannabis, methamphetamine, cocaine, heroin, oxycodone, hydrocodone, morphine, amphetamine and alprazolam. Design We pooled crowdsourced data from 2010-19 Price of Weed and 2010-19 StreetRx, and administrative data from the 2006-19 System to Retrieve Information from Drug Evidence (STRIDE) and the 2007-19 National Forensic Laboratory Information System (NFLIS). We employed a difference-in-differences design that exploited the staggered implementation of RCLs to compare changes in outcomes between RCL and non-RCL states. Setting and cases Eleven RCL and 40 non-RCL US states. Measures The primary outcome was the natural log of prices per gram, overall and by self-reported quality. The primary policy was an indicator of RCL implementation, defined using effective dates. Findings The street price of cannabis decreased by 9.2% [β = -0.092; 95% confidence interval (CI) = -0.15-, -0.03] in RCL states after RCL implementation, with largest declines among low-quality purchases (β = -0.195; 95% CI = -0.282, -0.108). Price declines were accompanied by a 93% (β = -0.93; 95% CI = -1.51, -0.36) reduction in law enforcement seizures of cannabis in RCL states. Among illegal opioids, including heroin, oxycodone and hydrocodone, street prices increased and law enforcement seizures decreased in RCL states. Conclusions Recreational cannabis laws in US states appear to be associated with illegal drug market responses in those states, including reductions in the street price of cannabis. Changes in the street prices of illegal opioids analyzed may suggest that in states with recreational cannabis laws the markets for other illegal drugs are not independent of legal cannabis market regulation.

Applications of differential subordination and superordination theorems to fluid mechanics involving a fractional higher-order integral operator

Abstract: The paper aims to study differential subordination and superordination preserving properties for certain analytic multivalent functions within the open unit disk related to a novel generalized fractional derivative operator for higher-order derivatives. As an application, we provide an explicit construction for the complex potential (the complex velocity) and the stream function of two-dimensional fluid flow problems over a circular cylinder using both vortex and source/sink. We further determine the fluid flow produced by a single source and construct a univalent function so that the image of a source is also a source for a given complex potential. Finally, we present some plot simulations that illustrate the results of this work.

Evaluation of the effect of isocyanate modification on the thermal and rheological properties of poly(ε-caprolactone)/cellulose composites

Abstract: Nanocellulose obtained with acid hydrolysis method using microcrystalline cellulose (MCC) was chemically modified with n-octadecyl isocyanate. Nanocellulose (NC), isocyanate modified nanocellulose (ISO-NC) and MCC were added to poly(e-caprolactone) (PCL) in order to produce composites by solvent casting method. Transmission electron microscopy (TEM) images showed that diameter of nanofibers ranged from 10 to 20 nm. The surface chemical modification of nanocellulose was characterized by Fourier-transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS). In order to understand the effect of cellulose content and modification on the performance of PCL/cellulose composites, surface morphologies, contact angle, thermal and rheological properties of the composites were investigated. The surface chemical modification with n-octadecyl isocyanate improved distribution of NC in PCL matrix. The dynamic mechanical and rheological properties of neat PCL were greatly improved by the addition of ISO-NC with respect to untreated NC and MCC due to the excellent interfacial compatibility between PCL and ISO-NC.