Skip to main content

Do Minimum Wage Increases Really Kill Jobs? Evidence from the "Fight for $15" Era

The debate over minimum wage policy has raged for decades, with economists, policymakers, and business leaders offering sharply different predictions about its effects on employment. Critics warn that raising the minimum wage will force employers to cut jobs, while supporters argue that higher wages boost worker productivity and spending power. But what does the actual data tell us. Using a comprehensive difference-in-differences analysis and Federal Reserve Economic Data covering 43 U.S. states from 2012-2020 of the "Fight for $15" movement between 2012 and 2020, I provide some evidence about how minimum wage increases actually affect employment in the real world.

The Perfect Natural Experiment

The period from 2012 to 2020 provided economists with an ideal "natural experiment" to study minimum wage effects. Here's why this timeframe was perfect for analysis:

  • Federal Stability: The federal minimum wage remained frozen at $7.25 per hour since 2009, creating a stable baseline for comparison.
  • State-Level Variation: The "Fight for $15" movement inspired 29 states to raise their minimum wages above the federal level, while 14 states kept theirs at $7.25.
  • Staggered Timing: States didn't all change their wages at once. Instead, they implemented increases in different years (2013-2020), allowing us to compare states before and after their policy changes.
  • Clean Controls: Unlike longer time periods that mix federal and state changes, this era gives us true "control" states that never raised their minimums.

The Data: A Comprehensive View

My analysis draws on high-quality federal economic data covering all 43 U.S. states from 2012 to 2020:

  • Employment Data: Monthly employment figures from the Federal Reserve Economic Data (FRED) system, aggregated to annual averages and converted to logarithmic form to measure percentage changes.
  • Minimum Wage Data: Official state minimum wage rates from FRED's comprehensive database, capturing all policy changes during this period.

Treatment Variation:
  • 29 states increased minimum wages above federal levels
  • 14 states maintained the $7.25 federal minimum throughout
  • Peak adoption years were 2013 (10 states) and 2014 (7 states)

The Method: Difference-in-Differences Analysis

To isolate the causal effect of minimum wage increases on employment, I used a "difference-in-differences" approach— common for policy evaluation in economics.

The Logic: Compare employment changes in states that raised minimum wages to employment changes in states that didn't, before and after the policy changes. This method controls for:

  • National economic trends affecting all states
  • Permanent differences between states
  • Other state-specific policies implemented at different times

Two Approaches:

  1. Two-Way Fixed Effects (TWFE): Estimates the average employment effect across all minimum wage increases
  2. Event Study: Tracks employment effects year-by-year around the time of policy adoption

Finding: Small Effects, Big Implications

The Overall Picture

Our analysis reveals that minimum wage increases during the "Fight for $15" era had small negative effects on employment:

  • TWFE Results: 1.6% decrease in employment (marginally significant, p = 0.0504)
  • Event Study: 0.83% decrease in the year of adoption (statistically significant, p = 0.0136)

The Event Study: A Detailed Timeline

The event study provides the most compelling evidence, tracking employment effects from 5 years before to 5 years after minimum wage adoption:

What This Graph Shows:

  • Pre-Treatment (Years -5 to -2): The flat, statistically insignificant coefficients confirm that treated and control states had similar employment trends before policy changes—validating our research design.
  • Year of Adoption (Year 0): A statistically significant drop of 0.83% in employment, shown by the negative coefficient that doesn't overlap with zero.
  • Post-Treatment (Years 1-5): Effects persist but become statistically indistinguishable from zero, suggesting either adaptation by businesses or statistical uncertainty due to smaller samples.
  • The Pattern: An immediate, modest employment reduction that appears to stabilize rather than compound over time.

Putting Results in Context

How Do These Findings Compare to Other Studies?

The results align closely with the modern economic consensus:

  • Similar Magnitudes: Recent high-quality studies find employment elasticities between 0.01 and 0.04, consistent with my findings.
  • Methodological Rigor: Unlike older studies that found larger effects, modern research using sophisticated methods (like my approach) consistently finds smaller impacts.
  • Meta-Analysis Support: When economists correct for publication bias—the tendency for journals to publish more dramatic results—the employment effects of minimum wages largely disappear.

The Economic Significance

While statistically detectable, these effects are economically modest:

  • Small Relative to Wage Gains: A 1.6% employment reduction is tiny compared to typical minimum wage increases of 15-30%.
  • Net Worker Benefits: For every 100 low-wage workers, roughly 98 keep their jobs with higher pay, while 2 might lose employment.
  • Aggregate Impact: The total income gained by workers receiving raises far exceeds income lost by those potentially losing jobs.

What This Means for Policy

The Case for Gradual Increases

Our findings support the approach taken by most "Fight for $15" states: gradual, predictable minimum wage increases. The data suggests:

  • Modest increases don't trigger mass layoffs
  • Businesses can adapt through productivity improvements, reduced turnover, or small price adjustments
  • Workers benefit substantially from higher wages with minimal employment risk

Addressing Common Concerns

  • "Job Killer" Claims: The data doesn't support predictions of massive job losses from minimum wage increases.
  • Small Business Impact: While some adjustment occurs, the effects are far smaller than often claimed by business groups.
  • Economic Growth: States that raised minimum wages didn't experience employment collapses or economic downturns.

Limitations and Future Research

What This Study Doesn't Capture

  • Substitution Effects: Our analysis measures net employment changes but may miss substitution between different types of workers.
  • Long-Term Effects: While I track effects for up to 5 years, even longer-term impacts remain uncertain.
  • Heterogeneous Effects: The impact likely varies across industries, regions, and demographic groups.

The Ongoing Debate

While my evidence supports modest minimum wage increases, the debate continues over:

  • Optimal minimum wage levels
  • Regional variation in appropriate wages
  • Alternative policies to support low-wage workers

The Bottom Line

The "Fight for $15" era provided a remarkable natural experiment in minimum wage policy, and the results are reassuring for supporters of higher wages. Minimum wage increases during 2012-2020 had small negative employment effects that were far outweighed by the benefits to workers who kept their jobs.

This doesn't mean minimum wages can be raised without limit—there's certainly some level that would cause substantial job losses. But the evidence suggests that the moderate increases implemented by most states during this period struck a reasonable balance between supporting workers and maintaining employment opportunities.

For policymakers considering minimum wage increases, the message is clear: done thoughtfully and gradually, minimum wage increases can improve worker welfare without devastating employment. The data supports continued experimentation with higher minimum wages, especially in high-cost regions where current wages provide inadequate living standards.


Full methodology and results are available upon request.

Comments

Popular posts from this blog

Malaysia at a Cross Roads: Diagnosing the Constraints to High Income Status

Malaysia at a Crossroads: Diagnosing Constraints to High-Income Status In 2008, Malaysia was recognized by the Growth Commission – a distinguished panel comprising 2 Nobel Prize Winning Economists and other leading development practitioners – as one of thirteen countries that sustained high growth in the post-war period. The 30-year stretch that caught the attention of the Growth Commission was between 1967 and 1997 when Malaysia grew at an average of 7.3% per year. This long stretch of growth was interrupted by periods of external shocks including the Volcker shock of 1986, the Asian Financial crisis in 1997/8, later the so-called Dot Com Bubble of 2001, and more recently the Global Financial Crisis of 2008. Despite these shocks, Malaysia remained resilient - formally earning the title "Upper Middle Income Country" in 1992. (See summary figure that breaks down the country's per capita growth story). As...

Corporate Network Analysis

The complex interconnections that define modern society are most readily visible from our Facebook, Twitter, or Linkedin networks. What is perhaps less talked about is the extent to which corporations are linked. I just started building a network of cross shareholding among Malaysia's corporations using listed company data. The map below is a preliminary visualization of the country's corporate network as of 2015. I use social network analysis (SNA) tools to partition or color the network into key connected components or communities therein. I have deliberately excluded company names but I will tell you that the biggest nodes represent the most connected shareholders including governments, fund managers, and international asset managers.  Malaysia's Corporate Network in 2015 Created Using Gephi 0.9.1 As the Malaysia economy has grown so has the complexity of the corporate network from few shareholders to many interlinked players. Below is a visualization using sha...

Assessing labor market transitions in Ghana using panel data

Understanding labor market transitions is important for policymakers and researchers in developing countries. Changes in economic activity status (employed, unemployed, out of labor force) vary significantly from one country to another and also within countries from one socio-economic group to another. Below I summarize analysis from the latest Ghana Annual Household Income and Expenditure Survey ( AHIES ) published by the Ghana Statistical Service. The AHIES is a panel survey that has followed over 10,000 individuals since 2022Q1 to assess changes in their livelihoods. I am currently analyzing trends and show here what has happened to economic activity between Q2 and Q3.  Transitions in Ghana labor force status, 2022Q2 - 2022Q3 Source : Own analysis using AHIES from Ghana Statistical Service. Note : Left hand side is 2022Q2 and right side is 2022Q3 81 percent of working age individuals (15-64-years) who were  employed  in 2022Q2 were still employed in 2022Q3; 7 perc...