NCS

2019

Assessing the effect of the federal overtime premium on hours worked

Leonard Goff

I am applying to use NCS data as a part of a research project on the causal effect of the FLSA overtime 

premium on weekly hours worked, as a part of my PhD dissertation. For this project, I have been 

fortunate to be provided with data on hours worked and wages at the paycheck level, from a payroll 

processing company. This fine-grained data allows me to exploit a “kink-design”, in which the effect of 

overtime can be plausibly elicited based upon how much the overtime premium adds to “bunching” at 

40 hours. However, to further investigate the underlying mechanisms for the estimated response by 

firms, it would be very useful to supplement this with information on other labor costs borne by firms 

that could come from the NCS. Additionally, access to the data would provide an opportunity for me to 

compare the representativeness of my payroll sample against the aggregated measures of weekly hours 

and wages from the NCS. Finally, indicators from the NCS of variation in overtime plans and the rate of 

FLSA exemption within sampled occupations would also be very helpful for my research design. In total, 

my project aims to test the hypothesis that federally mandated overtime pay causes firms to reduce 

weekly hours among non-exempt workers (and to quantify by how much), potentially substituting to 

hours from additional workers.

2018

Non-wage Benefits and Firms

Tania Babina, Paige Ouiment, Geoffrey Tate, & Liu Yang

In this paper, we propose to understand how non-wage benefits are utilized by firms to retain and 

attract skilled employees. We will examine how non-wage benefits impact employees by looking at the 

effect of these plans on employee turnover, wages and job satisfaction. We will also explore how nonwage benefits impact firms by looking at the effects of these plans on firm performance and labor force 

characteristics. We propose using both an OLS specification and an IV approach, where we will 

instrument for own firm’s non-wage benefits using non-wage offerings at peer firms. To conduct this 

analysis, we will merge data from the ECI/ECEC extract of the BLS National Compensation Survey (NCS) 

with Census data (project #1589) within the Federal Research Data Centers (FRDC). Non-wage benefits 

will be measured using cost estimates available in the ECI/ECEC extract. Census datasets will include the 

Longitudinal Business Database (LBD), the Longitudinal Employer-Household Dynamics database (LEHD), 

the Standard Statistical Establishment List (SSEL) and the Compustat-SSEL Bridge. External data will 

include Compustat data on publicly listed companies, available from WRDS, and GlassDoor data on 

employee reviews.

New Evidence on Compensation Volatility in the United States

GraceWeishi Gu & Eswar Prasad

This research project documents and analyzes the evolution of compensation volatility in the U.S., a key 

aspect of the broader debates on income inequality that is playing a crucial role in economic and 

political debates. We will examine not only wage volatility, as in the previous literature, but also the 
volatility of workers’ nonwage benefits and total compensation, a contribution that is unique to our 

study. Since nonwage benefits now account for one-third of labor compensation, our study adds an 

important new dimension to the existing literature on income volatility. This paper will also shed light on 

the roles of the Great Moderation and the recent financial crisis in affecting compensation uncertainty. 

We seek to use the disaggregated NCS data on hourly wage and benefit expenditures by establishment 

and job. Descriptive statistics will be used to characterize the evolution of wage and nonwage 

compensation variations. Multivariate analysis will be used to examine whether the compensation 

volatility patterns vary by establishment and occupational characteristics. No frequency counts shall be 

disclosed beyond the occupation or industry categories. This research project will have significant policy 

implications related to current debates about the uncertainty and inequality of labor income for U.S. 

workers.

2017

Downward Nominal Wage Rigidity in the United States During and After the Great Recession

Bruce Fallick, Daniel Villar & William Wascher

Rigidity in wages has long been thought to impede the functioning of labor markets. Such rigidity can 

take different forms, with differing implications for unemployment and other aspects of labor market or 

economic performance. Rigidities could arise from explicit or implicit contracting, efficiency wages, 

fixed-length nominal wage agreements, menu costs in the wage-setting process, government 

regulations, or informational or behavioral factors. 

One strand of the research on wage flexibility has focused on asymmetric rigidities in the nominal wagesetting process—most notably the downward nominal wage rigidity posited by Keynes (1936) and, later, 

Tobin (1972) —and what implications such rigidity might have for the macroeconomy at low levels of 

inflation. 

With consumer price inflation often running well over 5 percent in the 1970s and early 1980s, such 

concerns were seen as mostly immaterial—the costs of inflation were viewed as clearly exceeding any 

potential benefits. However, with inflation declining to 2 percent or less by the mid-1990s, the question 

of whether workers or firms resist nominal wage cuts—and the consequences for labor market 

performance—became increasingly relevant. The Great Recession of 2008-09, during which the 

unemployment rate reached 10 percent and price deflation was at times seen as a distinct possibility, 

added to the relevance of this line of inquiry. Indeed, some researchers have argued that downward 

nominal wage rigidity has had an important influence on the behavior of wage and price inflation in 

recent years (Daly and Hobijn 2014).

In this project, we use confidential micro data underlying the BLS’ Employment Cost Index to investigate 

the extent of downward nominal wage rigidity in U.S. labor markets, and how that rigidity may have 

changed during the Great Recession. Rather than restricting our analysis to a single method for 

estimating downward nominal wage rigidity, we use several distinct methods proposed in the literature 

to examine both the level of rigidity and how it has changed over time. With a particular focus on the 

Great Recession and subsequent slow recovery, we examine whether downward nominal wage rigidity 

is less or more severe at low rates of inflation and in the presence of negative economic shocks than in 

more normal economic times.
The Incidence of Mandated Paid Leave Benefits

Cameron LaPoint

Recent studies and policy reports have highlighted the importance of paid leave benefits for promoting 

public health and improving workplace productivity. However, little is known about who bears the costs 

of mandated paid leave benefits. I use NCS data from 2004-2016 and exploit the staggered 

implementation of state and city-level paid sick leave laws to examine the economic incidence of 

mandated paid sick time. In particular, by assigning establishments in the NCS to states and cities 

covered by a paid sick leave law, I ask whether mandates increase employer costs of providing leave 

benefits, and whether employers shift these costs to specific groups of workers by reducing wages or 

the generosity of other employee benefits. The results of this study will help explain findings in my 

previous work, where I showed that Google Trends search indices for vacation-related activities 

decrease by 15-30% after employees gain access to paid sick leave. If employers respond to sick pay 

laws by reducing the overall generosity of the paid leave benefits package, the unintended 

consequences of sick pay laws on vacation-taking could provide a rationale for benefits tax financing as 

an alternative to these mandates.

Using the NCS to Estimate the Impact of US Sick Pay Mandates on Sick Pay Coverage

Catherine Maclean & Nicolas Ziebarth

This proposal intends to use non-public labor market data from the National Compensation Survey (NCS) 

to test the following two hypotheses: (i) Sick pay mandates increase coverage rates. (ii) Sick pay 

mandates lead to substitution effects on other fringe benefits. In order to analyze these hypotheses, we 

require access to relevant NCS variables including all sick pay related questions, state identifiers, firm 

size, and industry as well as whether the establishment belongs to the private or public sector. Finally, 

we would need access to all variables containing information about other fringe benefits that the firm 

provides in order to test for potential substitution effects. Methodologically, the proposal intends to use 

Difference-in-Differences (DD) and Synthetic Control Group Methods (SCGM) to identify causal effects. A 

successful research proposal will result in one-two scientific working paper(s), which will be published in 

leading economic and/or health policy journals. In addition, we are planning to present the work at 

leading American and European international (health, labor, and public policy) economic conferences 

(e.g., American Society of Health Economists Biennial Conference, Association for Public Policy Analysis 

and Management Fall Research Conference, Society of Labor Economists Conference). The data output 

will consist of descriptive statistics in order to provide readers and policy makers an overview of the 

used data and the regression coefficients generated in a multivariate analysis when implementing the 

two above-noted methods to identify causal effects.