Tipping is large and growing, but we know little about its consequences for workers and firms. We link point-of-sale and payroll records at 20,000 U.S. firms, which lets us observe tips from customer payment to worker earnings. We find that tips are a nearly constant share of revenue, which means hourly pay moves with revenue. Firms that begin collecting tips claw back between 23 and 33 cents of each dollar of tips through lower base wages. Tips reward effort: workers at tipping firms earn more by serving more customers. We show this with demand shocks constructed from customer spending at other businesses. A demand shock raises revenue nearly twice as much at tipping firms as at non-tipping firms, while base wages and prices do not respond. Output per hour rises more despite a larger increase in hours. Effort drives the gap because each worker is more productive, so the firm expands and recovers about a third of the tips. Yet not every firm adopts tipping: the gain is smaller where customers tip less. A model calibrated to the demand-shock estimates implies that tipping benefits workers and firms, raising job value by about half and firm profit by about 30 percent in firms where customers are prone to tip. These gains may explain why tipping has recently grown in many industries.

Using point-of-sale and payroll data, we estimate the direct tax savings, behavioral tipping response, and incidence of the 2025 No Tax on Tips (NTOT) provision. The average tipped worker directly saves $531, but these savings are concentrated: 26% earn too little to benefit. Tip revenue rose 3.1% post-enactment as firms newly enabled tipping. Workers kept 72 cents of each new tip dollar, while firms lowered base pay by the remaining 28 cents. Overall, NTOT raised the average tipped worker's after-tax earnings by approximately 3.3%. The new tips are a raise for workers and, partly, a wage subsidy to firms.

A central question in immigration policy is how mobility restrictions affect the wages of temporary foreign workers (TFWs). We study the labor market return to TFWs gaining permanent residency (PR), which loosens mobility restrictions. Using administrative data linking matched employer-employee data in Canada to temporary and permanent visa records from 2004–2014 along with an event-study design, we find that gaining PR leads to a sharp, immediate, and persistent increase in the job switching rate of 21.7 percentage points and an increase in earnings of 3.2 percent three years after PR. These gains are driven primarily by reallocation across firms: workers move to higher-paying firms, and our estimates are consistent with no within-firm effects. To guide and interpret our reduced-form results, we develop a search-and-matching model featuring heterogeneous workers and firms. Permanent residents and native-born workers search for jobs in the same labor market and engage in on-the-job search, while TFWs search separately within a segmented labor market and do not receive outside wage offers. We calibrate the model to match our reduced-form results, and we use it to simulate the long-run effects of PR and consider two counterfactual policies: (1) increasing the cost to firms of posting a TFW vacancy and (2) allowing TFWs to switch employers freely under "open" visas. We evaluate how these policies affect output, wages, profits, and overall social welfare.

Economists disagree about the aggregate effects of the minimum wage and what they mean for basic economic theory. But, there is a mismatch between empirical evidence from policies that apply to entire markets and the textbook monopsony model that describes a single firm (Robinson, 1933). In this paper, we use new firm-level micro data on employment, wages, sales, and prices to study how low-wage employers adjust to minimum wage hikes. We find that firms paying just below the new minimum wage increase employment and lower prices relative to competitors, while firms already paying the old minimum do the opposite. This is new evidence that minimum wages increase employment and lower prices up to a threshold, above which the effects flip signs. Firms that are not directly affected also adjust because they compete with directly affected firms for both workers and customers. We interpret these results in a model of heterogeneous firms with both labor and product market power. We develop a general method to recover the model parameters from the difference-in-differences variation and find that unconstrained markups and markdowns are large. The market-level effects of the minimum wage depend on both the nature of firm-level heterogeneity and market-level spillovers. Spillovers, not reductions in firm-level monopsony markdowns, drive the bulk of employment and wage changes under the minimum wage policies we study.

We use novel administrative data covering thousands of small businesses to show that labor market frictions allow firms to impose an hours markdown and assign workers fewer hours than they would prefer at their current wage. When full-time workers leave a firm, their part-time coworkers immediately increase their hours at the same wage rate. Exploiting variation in schedule substitution patterns, we estimate that additional hours significantly reduce worker separations, revealing that workers prefer longer hours at their current wage. We interpret these findings in a simple model where search frictions allow (and incentivize) firms to maintain larger workforces as insurance against future separations, assigning fewer hours per worker. Our estimates imply that the median firm employs 25% more workers than the competitive benchmark, with an hours markdown of 20%.

Heterogeneity robust difference-in-differences methods typically require control units that remain untreated throughout the entire post-treatment window. This prevents the identification of long-run effects when researchers observe fewer pre-treatment periods than post-treatment periods. We show that cohort-stacked estimators identify long-run effects by chaining together successive not-yet-treated controls. This approach uses overlapping cohorts to extend identification under standard common trends assumptions. We apply this to the earnings effects of parenthood. In a setting where direct methods identify effects only four years post-birth, chaining extends identification to eight years.