The Atlanta Fed’s Wage Growth Tracker - wage-growth-data

Data - FRB

Info

Last observation: 2025-09-01 (N = 16)

First observation: 1997-03-01 (N = 16)

Last data update: 25 jul 2026, 14:18. Last compile: 17 aoû 2026, 22:39

date

`wage-growth-data` |>
  group_by(date) |>
  summarise(Nobs = n()) |>
  arrange(desc(date)) |>
  print_table_conditional()

variable

`wage-growth-data` |>
  group_by(variable) |>
  summarise(Nobs = n()) |>
  print_table_conditional()

variable	Nobs
Age 25-54	345
College degree	345
Female	345
Full-time	345
Job Stayer	345
Job Switcher	345
Lower 1/2 of wage distn	345
Male	345
Overall	345
Overall: 25/20 trimmed mean	345
Overall: Weekly Basis	345
Overall: Weighted	345
Overall: Weighted 97	345
Paid Hourly	345
Services	345
Upper 1/2 of wage distn	345

Leisure and Hospitality, Overall

Nominal

`wage-growth-data-industry` |>
  filter(variable %in% c("Leisure and hospitality", "Overall")) |>
  ggplot() + geom_line(aes(x = date, y = value/100, color = variable)) +
  theme_minimal() + ylab("Nominal Wage Growth (%)") + xlab("") +
  theme(legend.title = element_blank(),
        legend.position = c(0.85, 0.9)) +
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1993-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) +
  scale_color_manual(values = viridis(3)[1:2]) +
  scale_x_date(breaks = seq(1930, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 700, 1),
                     labels = scales::percent_format(accuracy = 1))

Real

`wage-growth-data-industry` |>
  filter(variable %in% c("Leisure and hospitality", "Overall")) |>
  left_join(inflation, by = "date") |>
  mutate(value = value - inflation) |>
  ggplot() + geom_line(aes(x = date, y = value/100, color = variable)) +
  theme_minimal() + ylab("Nominal Wage Growth (%)") + xlab("") +
  theme(legend.title = element_blank(),
        legend.position = c(0.85, 0.9)) +
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1993-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) +
  scale_color_manual(values = viridis(3)[1:2]) +
  scale_x_date(breaks = seq(1930, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 700, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed")

Services, Unweighted overall

Nominal

`wage-growth-data` |>
  filter(variable %in% c("Services", "Weighted Overall")) |>
  ggplot() + geom_line(aes(x = date, y = value/100, color = variable)) +
  theme_minimal() + ylab("Nominal Wage Growth (%)") + xlab("") +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.2)) +
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1993-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) +
  scale_color_manual(values = viridis(3)[1:2]) +
  scale_x_date(breaks = seq(1930, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 700, 1),
                     labels = scales::percent_format(accuracy = 1))

Real

`wage-growth-data` |>
  filter(variable %in% c("Services", "Weighted Overall")) |>
  left_join(inflation, by = "date") |>
  mutate(value = value - inflation) |>
  ggplot() + geom_line(aes(x = date, y = value/100, color = variable)) +
  theme_minimal() + ylab("Nominal Wage Growth (%)") + xlab("") +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.2)) +
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1993-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) +
  scale_color_manual(values = viridis(3)[1:2]) +
  scale_x_date(breaks = seq(1930, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 700, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed")

Job-stayer, Job-switcher

Nominal

`wage-growth-data` |>
  filter(variable %in% c("Job Stayer", "Job Switcher")) |>
  ggplot() + geom_line(aes(x = date, y = value/100, color = variable)) +
  theme_minimal() + ylab("Nominal Wage Growth (%)") + xlab("") +
  theme(legend.title = element_blank(),
        legend.position = c(0.85, 0.9)) +
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1993-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) +
  scale_color_manual(values = viridis(3)[1:2]) +
  scale_x_date(breaks = seq(1930, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 700, 1),
                     labels = scales::percent_format(accuracy = 1))

Real

`wage-growth-data` |>
  filter(variable %in% c("Job Stayer", "Job Switcher")) |>
  left_join(inflation, by = "date") |>
  mutate(value = value - inflation) |>
  ggplot() + geom_line(aes(x = date, y = (value)/100, color = variable)) +
  theme_minimal() + ylab("Real Wage Growth (%)") + xlab("") +
  theme(legend.title = element_blank(),
        legend.position = c(0.2, 0.2)) +
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1993-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) +
  scale_color_manual(values = viridis(3)[1:2]) +
  scale_x_date(breaks = seq(1930, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 700, 1),
                     labels = scales::percent_format(accuracy = 1)) +
  geom_hline(yintercept = 0, linetype = "dashed")

Full-time, Unweighted Overall

`wage-growth-data` |>
  filter(variable %in% c("Unweighted Overall", "Full-time")) |>
  ggplot() + geom_line(aes(x = date, y = value/100, color = variable)) +
  theme_minimal() + ylab("Wage Growth (%)") + xlab("") +
  theme(legend.title = element_blank(),
        legend.position = c(0.85, 0.9)) +
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1993-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) +
  scale_color_manual(values = viridis(3)[1:2]) +
  scale_x_date(breaks = seq(1930, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 700, 1),
                     labels = scales::percent_format(accuracy = 1))

Unweighted Overall

`wage-growth-data` |>
  filter(variable == "Unweighted Overall") |>
  ggplot() + geom_line(aes(x = date, y = value/100)) +
  theme_minimal() + ylab("Unweighted Overall Wage Growth (%)") + xlab("") +
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1993-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) +
  scale_x_date(breaks = seq(1930, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 700, 1),
                     labels = scales::percent_format(accuracy = 1))

Services, Unweighted Overall

`wage-growth-data` |>
  filter(variable == "Services") |>
  ggplot() + geom_line(aes(x = date, y = value/100)) +
  theme_minimal() + ylab("Services Wage Growth (%)") + xlab("") +
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1993-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) +
  scale_x_date(breaks = seq(1930, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 700, 1),
                     labels = scales::percent_format(accuracy = 1))

Full-time

`wage-growth-data` |>
  filter(variable == "Full-time") |>
  ggplot() + geom_line(aes(x = date, y = value/100)) +
  theme_minimal() + ylab("Full-time Wage Growth (%)") + xlab("") +
  geom_rect(data = nber_recessions |>
              filter(Peak > as.Date("1993-01-01")), 
            aes(xmin = Peak, xmax = Trough, ymin = -Inf, ymax = +Inf), 
            fill = 'grey', alpha = 0.5) +
  scale_x_date(breaks = seq(1930, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-100, 700, 1),
                     labels = scales::percent_format(accuracy = 1))