Unemployment Insurance Claims Research Articles

Unemployment Claims, COVID-19 Restrictions and Economic Support Measures in the U.S.

This paper considers the role of non-pharmaceutical interventions (NPIs) and economic support measures (ESM) in affecting excess unemployment insurance claims in the U.S. Using a panel Vector AutoRegressive specification, we find that unemployment claims are significantly affected by both policies (NPIs and ESM), and that economic support measures mitigate partially the negative labor market consequences of NPIs.

Unemployment insurance claims and COVID-19

We explore the effect of various factors on interstate differences in weekly unemployment insurance claims, focusing specifically on the determinants over the initial period of the pandemic in the U.S. We consider the effects of COVID-19 cases, state policies enacted in response to COVID-19, relevant provisions of Federal Coronavirus Aid, Relief and Economic Security (CARES) legislation, and the nature of state economies. We find that during the initial weeks of the pandemic, unemployment claims were driven by consumer reactions to the coronavirus. We find that over the March 21-April 25 period states with greater employment in industries most affected by the virus and which issued orders closing nonessential businesses experienced greater weekly unemployment claims. We find mixed evidence that unemployment benefits affect the number of unemployment claims. However, we find no evidence that the ability to work at home mitigated the increase in unemployment rates during this period, nor evidence that the CARES Act’s Payroll Protection Program influenced the level of new unemployment claims.

Delivering Unemployment Assistance in Times of Crisis

The COVID-19 public health emergency caused widespread economic shutdown and unemployment. The resulting surge in Unemployment Insurance claims threatened to overwhelm the legacy systems state workforce agencies rely on to collect, process, and pay claims. In Rhode Island, we developed a scalable cloud solution to collect Pandemic Unemployment Assistance claims as part of a new program created under the Coronavirus Aid, Relief and Economic Security Act to extend unemployment benefits to independent contractors and gig-economy workers not covered by traditional Unemployment Insurance. Our new system was developed, tested, and deployed within 10 days following the passage of the Coronavirus Aid, Relief and Economic Security Act, making Rhode Island the first state in the nation to collect, validate, and pay Pandemic Unemployment Assistance claims. A cloud-enhanced interactive voice response system was deployed a week later to handle the corresponding surge in weekly certifications for continuing unemployment benefits. Cloud solutions can augment legacy systems by offloading processes that are more efficiently handled in modern scalable systems, reserving the limited resources of legacy systems for what they were originally designed. This agile use of combined technologies allowed Rhode Island to deliver timely Pandemic Unemployment Assistance benefits with an estimated cost savings of $502,000 (representing a 411% return on investment).

Volunteerism in Times of Crisis: An Unconventional Response to Processing Unemployment Insurance Claims

This essay provides a reflective commentary outlining Hawai’i’s unconventional response for employing a volunteer workforce of public servants when faced with the task of processing an unprecedented backlog of unemployment insurance claims triggered by the COVID-19 pandemic. Although efforts are still ongoing, this essay applies volunteerism and public service motivation as a framework to explain why public servants would serve in a voluntary capacity at another public agency. The intent of this essay is to spur conversation on how public servants are further stepping up to the frontlines during times of crisis, as well as expand knowledge on the relationship between volunteerism and public service motivation.

Social Distancing, Labor Market Outcomes, and Job Characteristics in the COVID-19 Pandemic

This paper investigates the role of job characteristics on an individual's decisions to self-isolate, work, and apply for unemployment insurance in the US during the COVID-19 pandemic. We use data that track millions of mobile devices and their daily movements across physical locations to measure whether the mobile devices leave their homes, or part-time or full-time at work that day, and we also collect data on weekly unemployment insurance claims. We find that the presence of jobs with high work-from-home capacity in a region increases the ability of people to self-isolate and decreases their unemployment risk, whereas the presence of jobs with high physical proximity decreases the incidences of self-isolation and unemployment and increases the incidence of work during the pandemic. These heterogeneous responses based on local job characteristics persist even conditional on a broad set of demographic and socioeconomic variables.

US AND UK LABOUR MARKETS BEFORE AND DURING THE COVID-19 CRASH

We examine labour market performance in the US and the UK prior to the onset of the Covid-19 crash. We then track the changes that have occurred in the months and days from the beginning of March 2020 using what we call the Economics of Walking About (EWA) that shows a collapse twenty times faster and much deeper than the Great Recession. We examine unemployment insurance claims by state by day in the US as well as weekly national data. We track the distributional impact of the shock and show that already it is hitting the most vulnerable groups who are least able to work from home the hardest – the young, the least educated and minorities. We have no official labour market data for the UK past January but see evidence that job placements have fallen sharply. We report findings from an online poll fielded from 11–16 April 2020 showing that a third of workers in Canada and the US report that they have lost at least half of their income due to the Covid-19 crisis, compared with a quarter in the UK and 45 per cent in China. We estimate that the unemployment rate in the US is around 20 per cent in April. It is hard to know what it is in the UK given the paucity of data, but it has gone up a lot.

The Effects of COVID-19 on Unemployment Insurance Claims

The increase in unemployment insurance claims appears to be higher for states with relatively more employees in the service sector.

The Job Preservation Effects of Paycheck Protection Program Loans

The Paycheck Protection Program (PPP) covered in excess of 80% of eligible U.S. small businessemployment, supporting 51 million American jobs through the program’s close on August 8th,2020. Of those supported jobs, how many would have been lost in the absence of PPP loans?To answer this question, we propose an empirical strategy to identify the effects of PPP loanson county-level unemployment insurance claims. Specifically, we exploit variation in the timingof loan receipt caused by differences in local banking market structure across US counties. Onthe margin, we estimate that a 10 percentage point increase in eligible payroll covered by PPPresulted in a 1 to 2 percentage point smaller jump in weekly initial unemployment insurance(UI) claims, as a share of employment covered by UI. With a lag, that same 10 percentagepoint increase in PPP coverage resulted in an estimated 5 percentage point smaller increasein the insured unemployment rate. In order to compare our estimates with related studies,we calculate an aggregate employment effect of PPP loans. Moving from the 25th percentileto 75th percentile of counties by early PPP coverage causes an improvement in the insuredunemployment rate of over 12 percentage points, or, extrapolated nationally, 18.6 million jobs.We note meaningful caveats to interpreting this paper’s aggregate number; the same caveats thatapply to other papers evaluating PPP loans. This paper’s estimates are an order of magnitudelarger than previous evaluations of PPP, which have tended to find small employment effects ornone at all.

Which Earnings Groups Have Been Most Affected by the COVID-19 Crisis?

The [Coronavirus Disease 2019] COVID-19 crisis has had unprecedented negative effects on the aggregate US economy, but especially on the labor market. The unemployment rate jumped from 3.5 per cent to 14.7 per cent between February and April and only slightly decreased to 13.3 per cent in May. Fifty million initial unemployment insurance (UI) claims have been filed so far this year, which is about 10 million more than total initial UI claims filed during the Great Recession. Besides its aggregate effects on the labor market, the COVID-19 crisis has had disproportionate effects on certain individuals. In this essay, we explore the differential labor market impacts across the earnings distribution.

Job Losses During the Onset of the COVID-19 Pandemic: Stay-at-home Orders, Industry Composition, and Administrative Capacity

Six weeks after the national emergency declaration for the COVID-19 pandemic, unemployment insurance (UI) claims as a share of total state employment differed by as much as 24 percentage points across states. This paper examines three explanations for these dramatic differences: statewide stay-at-home orders, the industry composition of states' employment, and the historical utilization of states' UI systems. We find that i) the surge in UI claims began and often peaked before states enacted stay-at-home orders; ii) relative to other states, states that would eventually enact stay-at-home orders had high UI claim rates before the orders were enacted; iii) six weeks after the national emergency declaration, statewide stay-at-home orders accounted for less than 30% of the difference in cumulative initial UI claims between states that ever-versus-never enacted statewide stay-at-home orders; iv) industry-related exposure to the COVID-19 pandemic can account for twice as much of the state-level variation in UI claims relative to stay-at-home orders; and v) states with greater historical utilization of their UI systems by unemployed workers tended to both receive more UI claims and process these claims more quickly at the onset of the COVID-19 pandemic.

Nowcasting unemployment insurance claims in the time of COVID-19

Near term forecasts, also called nowcasts, are most challenging but also most important when the economy experiences an abrupt change. In this paper, we explore the performance of models with different information sets and data structures in order to best nowcast US initial unemployment claims in spring of 2020 in the midst of the COVID-19 pandemic. We show that the best model, particularly near the structural break in claims, is a state-level panel model that includes dummy variables to capture the variation in timing of state-of-emergency declarations. Autoregressive models perform poorly at first but catch up relatively quickly. Models including Google Trends are outperformed by alternative models in nearly all periods. Our results suggest that in times of structural change there is a bias-variance tradeoff. Early on, simple approaches to exploit relevant information in the cross sectional dimension improve forecasts, but in later periods the efficiency of autoregressive models dominates.

Impact of Welfare Benefit Sanctioning on Food Insecurity: a Dynamic Cross-Area Study of Food Bank Usage in the UK

AbstractSince 2009, the UK has witnessed marked increases in the rate of sanctions applied to unemployment insurance claimants, as part of a wider agenda of austerity and welfare reform. In 2013, over one million sanctions were applied, stopping benefit payments for a minimum of four weeks and potentially leaving people facing economic hardship and driving them to use food banks. Here we explore whether sanctioning is associated with food bank use by linking data from The Trussell Trust Foodbank Network with records on sanctioning rates across 259 local authorities in the UK. After accounting for local authority differences and time trends, the rate of adults fed by food banks rose by an additional 3.36 adults per 100,000 (95% CI: 1.71 to 5.01) as the rate of sanctioning increased by 10 per 100,000 adults. The availability of food distribution sites affected how tightly sanctioning and food bank usage were associated (p< 0.001); in areas with few distribution sites, rising sanctions led to smaller increases in food bank usage. In conclusion, sanctioning is closely linked with rising food bank usage, but the impact of sanctioning on household food insecurity is not fully reflected in available data.

Forecasting Macroeconomic Labour Market Flows: What Can We Learn from Micro‐level Analysis?

AbstractForecasting labour market flows is important for budgeting and decision‐making in government departments and public administration. Macroeconomic forecasts are normally obtained from time series data. In this article, we follow another approach that uses individual‐level statistical analysis to predict the number of exits out of unemployment insurance claims. We present a comparative study of econometric, actuarial and statistical methodologies that base on different data structures. The results with records of the German unemployment insurance suggest that prediction based on individual‐level statistical duration analysis constitutes an interesting alternative to aggregate data‐based forecasting. In particular, forecasts of up to six months ahead are surprisingly precise and are found to be more precise than considered time series forecasts.

Decreasing Improper Payments in a Complex Federal Program

AbstractSince the early 2000s, the U.S. federal government has placed increasing focus on combating improper payments. Implementing policies to control improper payments is no easy task. Federal programs are often large, complex, riddled with moral hazard concerns, and jointly implemented. In 2011, the U.S. Department of Labor adopted a national strategy to combat improper payments in the Unemployment Insurance program. This article examines the effect that the Department of Labor's strategic initiative had on lowering states’ improper payments. Findings show that two of its tools—mandatory cross matching of employment records between the National Directory of New Hires and State Directories of New Hires and a communication strategy known as messaging—played a statistically significant role in halting the rise of improperly paid unemployment insurance claims. These results suggest that information technology tools and increased communication among stakeholders can be effective in lowering improper payments and improving government performance.

The Level of Service Quality and Customer Satisfaction of the Insurance Industries in Indonesia

This survey aims to investigate the level of service quality, client satisfaction and the image of Indonesia in particular insurance companies to PT (Limited Liability Company) Insurance Bumiputera Bumida Palembang. Indirectly influence the quality of services to the corporate image through satisfaction. The method used was descriptive. Data obtained through the distribution of questionnaires to 285 unemployment insurance claims losses Bumida Palembang PT Asuransi Bumiputera study. Descriptive analysis that involves frequencies, means and percentages used in this study. The results showed that the effect of simultaneous five dimensions of service quality are tangible, reliability, responsiveness, assurance and empathy are positive and significant on unemployment claims satisfaction of 49.7%. In partial, reliability dimension has an important influence positively the most dominant to the satisfaction of jobless claims, which accounted for 27%, the next dimension significantly, dimensions responsiveness, assurance dimensions and dimensions of empathy has had a major influence positively to the satisfaction of unemployment claims that each by 21.5, 20.6, 18.1 and 19.6% of each other. Five dimensions of service quality has an indirect effect a positive image of the company PT Asuransi Palembang Bumida Bumiputera through satisfaction jobless claims, which are tangibles is 2.3%, dimensional reliability is 2.9%, dimensions responsiveness is 2.2%, dimensions guarantee is 1.9% and empathy dimension it amounted to 2.1%. Although unemployment claims satisfaction in handling insurance claims loss solutions have a positive effect and significant to the company's image is equal to 10.7%.

The Adversarial Process of Administrative Claims

Although administrative hearings are not formal litigation, the process often resembles traditional adversarial adjudication. There are two parties, one has the burden of proof, both present evidence, and there is a ruling on the legal merits. Substantively, the hearing focuses on eligibility for benefits. Procedurally, the hearing runs like traditional courtroom litigation. Based on direct observation of 45 unemployment insurance claims and interviews with administrative law judges (ALJs), I find ALJs behave differently when there is no legal counsel present. Whereas the law that governs the hearing remains the same, the process for pro se claimants is substantively different.

Workplace Experiences and Unemployment Insurance Claims: How Personal Relationships and the Structure of Work Shape Access to Public Benefits

AbstractWhat influences whether unemployed individuals take up Unemployment Insurance (UI)? For answers to this question, research on the take-up of public benefits has looked to the individual gov...

Optimal Formulations for Nonlinear Autoregressive Processes

We develop optimal formulations for nonlinear autoregressive models by representing them as linear autoregressive models with time-varying temporal dependence coefficients. We propose a parameter updating scheme based on the score of the predictive likelihood function at each time point. The resulting time-varying autoregressive model is formulated as a nonlinear autoregressive model and is compared with threshold and smooth-transition autoregressive models. We establish the information theoretic optimality of the score driven nonlinear autoregressive process and the asymptotic theory for maximum likelihood parameter estimation. The performance of our model in extracting the time-varying or the nonlinear dependence for finite samples is studied in a Monte Carlo exercise. In our empirical study we present the in-sample and out-of-sample performances of our model for a weekly time series of unemployment insurance claims.

Dynamic Threshold Modelling and the US Business Cycle

Summary Leading economic indicators are often used to anticipate changes in key economic variables. Understanding the dynamics of these indicators is of primary interest for policy-making objectives and for sustainable economic welfare. We are concerned with the problem of setting a dynamic threshold above which the value of leading indicators would be considered as extreme. We propose a dynamic threshold modelling approach based on fractionally integrated processes where a semiparametric method is used to determine the amount of differencing that is required to obtain a weakly stationary process—to which standard methods of statistics of extremes apply. Given that our approach is linked to the Box–Jenkins method, we refer to the procedure proposed and applied herein as the Box–Jenkins–Pareto procedure. We use our approach to analyse the weekly number of unemployment insurance claims in the USA and explore the connection between its threshold exceedances and the US business cycle.

Tortious Interference with the Expectancy of Entitlement Benefits

This Note proposes a new tort to address employers' and their agents' increasing abuse of the Unemployment Insurance appeals process, which interferes with employees' expectancy of entitlement benefits. Though existing state Unemployment Compensation statutes sanction both unemployed workers claiming benefits and employers for making fraudulent statements, these provisions approach the issue of fraud too narrowly to combat this growing problem. Meanwhile, no existing remedy properly compensates victims of this sort of abuse, adequately deters abusive behavior by scaling the penalty to the harm, and is accessible to economically disadvantaged plaintiffs. As well as providing an analysis of the specific problem of abuse of the appeals process in the Unemployment Compensation arena, this Note also aspires to provide the framework for a compelling legal argument that such abuse should trigger tort liability in the hopes of easing the work of any public interest attorney interested in bringing such a suit. Although this Note focuses on Unemployment Insurance claims, the principles discussed are generally applicable to a variety of other entitlement benefit claims. Part I identifies the employer behavior that presents the need for a remedy in tort. Part II articulates the criteria for an adequate remedy. Part III examines potential legal remedies to the problem of abusive appeals by employers during the claim and appeals process and finds them inadequate to protect the pressing economic interests of claimants and society. Part IV proposes the recognition of a new tort to fill this gap, and details both the grounds for liability and the computation of damages flowing from this form of liability.