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Tag Archives: Statistics awareness

Improving Key Labor Market Estimates during the Pandemic and Beyond

If things were good enough yesterday, why would we change them today? Good enough is OK for folding laundry, cleaning the junk drawer, and raking leaves, but not for official statistics from BLS. We do our best to provide a timely look at the labor market and economy, but we often learn more after we publish those initial data. As a result, we sometimes revise our statistics. That’s mostly a good thing, but there is a fine line between the frequency of revisions and introducing noise and possibly confusion.

I recently wrote about the importance of maintaining and sometimes changing official historical records, using baseball as an example. Today I want to highlight two of our statistical programs: the Job Openings and Labor Turnover Survey (JOLTS) and the Local Area Unemployment Statistics (LAUS) data. We publish monthly statistics from these programs and revise them the following month as more information comes in. In addition to the monthly revisions, we incorporate more information once a year.

The COVID-19 pandemic continues to have a huge impact on our lives. Check out our summary of how the pandemic affected the labor market and economy in 2020. The magnitude of the labor market changes stress tested the JOLTS and LAUS programs. Based on what we observed in real time, and what we know now, we realized we needed to respond to this unusual economic environment. We change our estimating techniques infrequently, but even the best techniques need adjustments to respond to such significant shocks. These adjustments reflect our commitment to continuous improvement.

Changes in Job Openings and Labor Turnover Estimates

The economic conditions caused by the pandemic led us to make two changes to JOLTS procedures. First, we changed the way we handled unusual reports, which we call outliers. In normal times, these outliers may be businesses with unusually large numbers of job separations. This process mutes the outlier impact on the estimates because those outliers are unlikely to represent other businesses. At the start of the pandemic, however, very large increases in separations were followed by very large increases in hires in many businesses. During this period, we adjusted the JOLTS outlier-detection techniques to accept as normal those extreme changes. Under these circumstances, these “outlier” reports did in fact represent many other businesses.

Second, JOLTS uses data from the much larger Current Employment Statistics (CES) sample to adjust estimates of hires and separations to stay in sync with the monthly employment changes. This procedure assumes that, over the long term, the difference between JOLTS hires and separations is close to the CES employment change. This assumption, however, was not appropriate in late March 2020 as people, businesses, and governments tried to contain the spread of COVID-19. The two surveys have different reference periods. The CES reference period is the pay period that includes the 12th of the month, whereas JOLTS estimates of hires and separations cover the entire month. Hires and separations during the latter half of March 2020 were not included in the CES employment change for March but were included in the JOLTS estimates for the month. To accurately capture the timing of this unprecedented event, we stopped aligning the JOLTS estimates of hires and separations with the CES employment change from March through November 2020.

More changes to JOLTS estimates came with the publication of the January 2021 news release. As we do every year, we revised the past 5 years of historical JOLTS data using updated CES employment estimates. We also updated the seasonal adjustment factors and applied them over the past 5 years. In addition, because we stopped using the alignment procedure for most of 2020, the difference between CES and JOLTS estimates had become quite large by December. To preserve the true economic differences between CES and JOLTS but reduce the divergence by the end of 2020, we adjusted estimates of hires and separations for the months in which the alignment procedure was turned off. These adjustments ensure that we report the highest quality data as quickly as we can, while improving accuracy as we learn more information.

Changes in State Labor Force and Unemployment Estimates

We also made real-time changes during the pandemic to the models we use to produce state labor force and unemployment estimates. The primary inputs to the models are from the Current Population Survey (CPS), the source of the monthly national unemployment rate and other labor market measures. Because the CPS sample is not large enough to support state estimates on a monthly basis, we also use CES employment data and counts of continued claims for unemployment insurance to help inform the models. All of these model inputs experienced extreme movements, especially in the early part of the pandemic.

Starting with March 2020, we introduced two monthly adjustments we usually perform only once a year. These adjustments involved closer review and adjustment of outliers from all model inputs and level shifts. We discussed these changes in notes that appeared in the State Employment and Unemployment news releases for March 2020, April 2020, and May 2020.

These changes in 2020 provided a short-term solution for the state models. For the longer term, we respecified the relationships of the model inputs to provide more flexibility when unusual disruptions occur in the labor market. We explain these changes in our “Questions and Answers.”

We implemented the new estimation procedures for model-based areas in early 2021. They were reflected in the estimates published in the Regional and State Unemployment – 2020 Annual Averages news release. We replaced all previously published state data using the new procedures to ensure historically comparable estimates. The recent data revisions also reflect the best available inputs for model estimation. If you are interested in the details, you can read all about them at the LAUS Estimation Methodology page.

The speed with which the JOLTS and LAUS staff researched and implemented these improvements reflects the high quality of the BLS staff and their commitment to producing gold standard data. They make me proud to lead this great agency.

Looking Back on the 2020 U.S. Labor Market and Economy

I know many of us are glad to see 2020 in the rearview mirror and have higher hopes for 2021. The COVID-19 pandemic has caused so much suffering and hardship for people in the United States and around the world. During these challenging times, it remains important to have good, reliable, timely data. Good data are essential for the public health response to the pandemic and for tracking its economic and social effects, as well as the progress toward recovery. Let’s reflect back on some of the historic measures we saw in 2020.

Throughout the pandemic, the BLS staff and our colleagues across the statistical community have remained on the job to meet the growing needs for high-quality data. We are thankful we have been able to keep working; millions of other people haven’t been so fortunate. In part this is due to the way our work life at BLS changed in 2020. Nearly the entire staff has teleworked full time since March. That means we have needed to figure out new ways to collaborate with each other to continue producing essential data about the economy. That change in work life also meant that many staff members faced the challenges of new care arrangements for young children, schooling—often online—for older children, and keeping all their loved ones safe and healthy.

When the pandemic began in March 2020, many consumers began avoiding stores, restaurants, and other public gatherings to reduce the risk of catching or spreading the virus that causes COVID-19. Many businesses and other organizations reduced their operations or closed completely. At the recommendation of public health authorities, many governors and other public leaders issued stay-at-home orders. The economic impact of COVID-19 was breathtaking in its speed and severity.

National employment data. The nation experienced steady employment growth in recent years; BLS recorded average monthly increases in nonfarm employment between about 170,000 and 200,000 from 2016 to 2019. January and February 2020 brought continued job gains before the bottom dropped out in March (down 1.7 million jobs) and especially in April (down 20.7 million). These were the two largest declines in history, dating to 1939. These declines were then followed by the 4 largest increases in history: 2.8 million, 4.8 million, 1.7 million, and 1.5 million. You have to go back to 1983 to find the next highest increase, 1,118,000. Employment in December 2020 was nearly 10 million lower than in February.

Nonfarm payroll employment, January 1970–December 2020

Editor’s note: Data for this chart are available in the table below.

National unemployment data. The year started with some record-low unemployment rates. The 3.5-percent unemployment rate in both January and February 2020 tied for the lowest rate since December 1969 (also 3.5 percent). The unemployment rates for several demographic groups were at or near their record lows. For example, the unemployment rate for African Americans in February 2020, at 6.0 percent, was close to the all-time low of 5.2 percent in August 2019.

Then came the pandemic in March 2020. The unemployment rate that month rose 0.9 percentage point to 4.4 percent. In April, the unemployment rate increased by 10.4 percentage points to 14.8 percent, the highest rate and largest one-month increase in history (dating to January 1948). Nearly all demographic groups experienced record-high unemployment rates in April; for example, the rate for Hispanics was a record 18.9 percent, after a record low of 4.0 percent in September 2019. And for the first time since data became available for both groups in 1973, the unemployment rate for Hispanics in April 2020 exceeded the rate for African Americans.

Unemployment rates for selected groups, February, April, and December 2020

Editor’s note: Data for this chart are available in the table below.

State unemployment data. We see a similar pattern when looking at state unemployment rates, with record-setting lows early in 2020 followed by record-setting highs. In February, state unemployment rates ranged from a low of 2.2 percent in North Dakota to a high of 5.8 percent in Alaska, with 12 states at their historic lows that month. By April, rates had increased in all states, with 40 states and the District of Columbia setting new highs in that month, and another 7 states cresting in subsequent months. (The state data began in 1976.) State unemployment rates in April ranged from 8.3 percent in Connecticut to 30.1 percent in Nevada. Check out our animated map showing the rapid transformation of state unemployment rates.

Consumer price data. Beyond the job market, the pandemic had a big effect on other aspects of everyday life, including consumers’ buying habits. Toilet paper and wipes were disappearing from store shelves, while fewer people were commuting or traveling. Those trends were reflected in rapid changes in consumer prices.

One-month changes in the Consumer Price Index are typically 0.1 or 0.2 percent; the 0.8 percent decrease in April 2020, was the largest monthly decline since December 2008. The overall change included some large movements in both directions. For example, the price of gasoline declined 20.6 percent in April, the largest one-month decline since November 2008. In contrast, prices for food at home rose by 2.6 percent, the largest monthly increase since February 1974. Looking below the surface even further, several items experienced record one-month price changes, with some records going back over 50 years.

Percent change in consumer prices for selected items in April 2020, seasonally adjusted

Editor’s note: Data for this chart are available in the table below.

Labor Productivity data. The BLS quarterly measure of labor productivity in the nonfarm business sector compares output to hours worked. If output rises more than hours worked, productivity increases. The pandemic saw large declines in both output and hours starting in mid-March. There was a small decline in labor productivity in the first quarter of 2020, down 0.3 percent, as output declined (-6.4 percent) slightly more than hours worked (-6.1 percent). While we had not experienced declining productivity in nearly 3 years, small increases or decreases in the quarterly change are common. The second quarter saw labor productivity soar by 10.6 percent, the largest increase since 1971, when productivity increased 12.3 percent in the first quarter. The second quarter 2020 increase reflected a greater decline in hours worked (-42.9 percent) than in output (-36.8 percent).

Since its beginnings in 1884, BLS has built consistent data to allow comparisons across the decades. Maintaining this history allows data users to quickly learn “when was the last time.” We also have collected and published new data specifically about the COVID-19 pandemic. Still to come, BLS will release more 2020 data in the coming year. Those new results will add to the unique story of the extraordinary 2020 economy.

Nonfarm payroll employment, January 1970–December 2020
MonthEmployment levelOver-the-month change

Jan 1970

71,176,000-65,000

Feb 1970

71,305,000129,000

Mar 1970

71,451,000146,000

Apr 1970

71,348,000-103,000

May 1970

71,124,000-224,000

Jun 1970

71,029,000-95,000

Jul 1970

71,053,00024,000

Aug 1970

70,937,000-116,000

Sep 1970

70,944,0007,000

Oct 1970

70,521,000-423,000

Nov 1970

70,409,000-112,000

Dec 1970

70,792,000383,000

Jan 1971

70,865,00073,000

Feb 1971

70,807,000-58,000

Mar 1971

70,860,00053,000

Apr 1971

71,036,000176,000

May 1971

71,247,000211,000

Jun 1971

71,254,0007,000

Jul 1971

71,315,00061,000

Aug 1971

71,373,00058,000

Sep 1971

71,614,000241,000

Oct 1971

71,642,00028,000

Nov 1971

71,847,000205,000

Dec 1971

72,109,000262,000

Jan 1972

72,441,000332,000

Feb 1972

72,648,000207,000

Mar 1972

72,944,000296,000

Apr 1972

73,162,000218,000

May 1972

73,469,000307,000

Jun 1972

73,758,000289,000

Jul 1972

73,709,000-49,000

Aug 1972

74,141,000432,000

Sep 1972

74,264,000123,000

Oct 1972

74,674,000410,000

Nov 1972

74,973,000299,000

Dec 1972

75,268,000295,000

Jan 1973

75,617,000349,000

Feb 1973

76,014,000397,000

Mar 1973

76,284,000270,000

Apr 1973

76,455,000171,000

May 1973

76,648,000193,000

Jun 1973

76,887,000239,000

Jul 1973

76,913,00026,000

Aug 1973

77,168,000255,000

Sep 1973

77,276,000108,000

Oct 1973

77,607,000331,000

Nov 1973

77,920,000313,000

Dec 1973

78,031,000111,000

Jan 1974

78,100,00069,000

Feb 1974

78,254,000154,000

Mar 1974

78,296,00042,000

Apr 1974

78,382,00086,000

May 1974

78,549,000167,000

Jun 1974

78,604,00055,000

Jul 1974

78,636,00032,000

Aug 1974

78,619,000-17,000

Sep 1974

78,610,000-9,000

Oct 1974

78,630,00020,000

Nov 1974

78,265,000-365,000

Dec 1974

77,652,000-613,000

Jan 1975

77,293,000-359,000

Feb 1975

76,918,000-375,000

Mar 1975

76,648,000-270,000

Apr 1975

76,460,000-188,000

May 1975

76,624,000164,000

Jun 1975

76,521,000-103,000

Jul 1975

76,770,000249,000

Aug 1975

77,153,000383,000

Sep 1975

77,228,00075,000

Oct 1975

77,540,000312,000

Nov 1975

77,685,000145,000

Dec 1975

78,017,000332,000

Jan 1976

78,503,000486,000

Feb 1976

78,816,000313,000

Mar 1976

79,048,000232,000

Apr 1976

79,292,000244,000

May 1976

79,312,00020,000

Jun 1976

79,376,00064,000

Jul 1976

79,547,000171,000

Aug 1976

79,704,000157,000

Sep 1976

79,892,000188,000

Oct 1976

79,911,00019,000

Nov 1976

80,240,000329,000

Dec 1976

80,448,000208,000

Jan 1977

80,690,000242,000

Feb 1977

80,988,000298,000

Mar 1977

81,391,000403,000

Apr 1977

81,728,000337,000

May 1977

82,088,000360,000

Jun 1977

82,488,000400,000

Jul 1977

82,834,000346,000

Aug 1977

83,075,000241,000

Sep 1977

83,532,000457,000

Oct 1977

83,800,000268,000

Nov 1977

84,173,000373,000

Dec 1977

84,410,000237,000

Jan 1978

84,594,000184,000

Feb 1978

84,948,000354,000

Mar 1978

85,460,000512,000

Apr 1978

86,162,000702,000

May 1978

86,509,000347,000

Jun 1978

86,950,000441,000

Jul 1978

87,204,000254,000

Aug 1978

87,483,000279,000

Sep 1978

87,621,000138,000

Oct 1978

87,956,000335,000

Nov 1978

88,391,000435,000

Dec 1978

88,671,000280,000

Jan 1979

88,808,000137,000

Feb 1979

89,055,000247,000

Mar 1979

89,479,000424,000

Apr 1979

89,417,000-62,000

May 1979

89,789,000372,000

Jun 1979

90,108,000319,000

Jul 1979

90,217,000109,000

Aug 1979

90,300,00083,000

Sep 1979

90,327,00027,000

Oct 1979

90,481,000154,000

Nov 1979

90,573,00092,000

Dec 1979

90,672,00099,000

Jan 1980

90,800,000128,000

Feb 1980

90,883,00083,000

Mar 1980

90,994,000111,000

Apr 1980

90,849,000-145,000

May 1980

90,420,000-429,000

Jun 1980

90,101,000-319,000

Jul 1980

89,840,000-261,000

Aug 1980

90,099,000259,000

Sep 1980

90,213,000114,000

Oct 1980

90,490,000277,000

Nov 1980

90,747,000257,000

Dec 1980

90,943,000196,000

Jan 1981

91,033,00090,000

Feb 1981

91,105,00072,000

Mar 1981

91,210,000105,000

Apr 1981

91,283,00073,000

May 1981

91,296,00013,000

Jun 1981

91,490,000194,000

Jul 1981

91,601,000111,000

Aug 1981

91,565,000-36,000

Sep 1981

91,477,000-88,000

Oct 1981

91,380,000-97,000

Nov 1981

91,171,000-209,000

Dec 1981

90,895,000-276,000

Jan 1982

90,565,000-330,000

Feb 1982

90,563,000-2,000

Mar 1982

90,434,000-129,000

Apr 1982

90,150,000-284,000

May 1982

90,107,000-43,000

Jun 1982

89,865,000-242,000

Jul 1982

89,521,000-344,000

Aug 1982

89,363,000-158,000

Sep 1982

89,183,000-180,000

Oct 1982

88,907,000-276,000

Nov 1982

88,786,000-121,000

Dec 1982

88,771,000-15,000

Jan 1983

88,990,000219,000

Feb 1983

88,917,000-73,000

Mar 1983

89,090,000173,000

Apr 1983

89,364,000274,000

May 1983

89,644,000280,000

Jun 1983

90,021,000377,000

Jul 1983

90,437,000416,000

Aug 1983

90,129,000-308,000

Sep 1983

91,247,0001,118,000

Oct 1983

91,520,000273,000

Nov 1983

91,875,000355,000

Dec 1983

92,230,000355,000

Jan 1984

92,673,000443,000

Feb 1984

93,157,000484,000

Mar 1984

93,429,000272,000

Apr 1984

93,792,000363,000

May 1984

94,098,000306,000

Jun 1984

94,479,000381,000

Jul 1984

94,789,000310,000

Aug 1984

95,032,000243,000

Sep 1984

95,344,000312,000

Oct 1984

95,629,000285,000

Nov 1984

95,982,000353,000

Dec 1984

96,107,000125,000

Jan 1985

96,372,000265,000

Feb 1985

96,503,000131,000

Mar 1985

96,842,000339,000

Apr 1985

97,038,000196,000

May 1985

97,312,000274,000

Jun 1985

97,459,000147,000

Jul 1985

97,648,000189,000

Aug 1985

97,840,000192,000

Sep 1985

98,045,000205,000

Oct 1985

98,233,000188,000

Nov 1985

98,443,000210,000

Dec 1985

98,609,000166,000

Jan 1986

98,732,000123,000

Feb 1986

98,847,000115,000

Mar 1986

98,934,00087,000

Apr 1986

99,121,000187,000

May 1986

99,248,000127,000

Jun 1986

99,155,000-93,000

Jul 1986

99,473,000318,000

Aug 1986

99,588,000115,000

Sep 1986

99,934,000346,000

Oct 1986

100,121,000187,000

Nov 1986

100,308,000187,000

Dec 1986

100,509,000201,000

Jan 1987

100,678,000169,000

Feb 1987

100,919,000241,000

Mar 1987

101,164,000245,000

Apr 1987

101,499,000335,000

May 1987

101,728,000229,000

Jun 1987

101,900,000172,000

Jul 1987

102,247,000347,000

Aug 1987

102,420,000173,000

Sep 1987

102,647,000227,000

Oct 1987

103,138,000491,000

Nov 1987

103,372,000234,000

Dec 1987

103,661,000289,000

Jan 1988

103,753,00092,000

Feb 1988

104,214,000461,000

Mar 1988

104,489,000275,000

Apr 1988

104,732,000243,000

May 1988

104,962,000230,000

Jun 1988

105,326,000364,000

Jul 1988

105,550,000224,000

Aug 1988

105,674,000124,000

Sep 1988

106,013,000339,000

Oct 1988

106,276,000263,000

Nov 1988

106,617,000341,000

Dec 1988

106,898,000281,000

Jan 1989

107,161,000263,000

Feb 1989

107,427,000266,000

Mar 1989

107,621,000194,000

Apr 1989

107,791,000170,000

May 1989

107,913,000122,000

Jun 1989

108,027,000114,000

Jul 1989

108,069,00042,000

Aug 1989

108,120,00051,000

Sep 1989

108,369,000249,000

Oct 1989

108,476,000107,000

Nov 1989

108,752,000276,000

Dec 1989

108,836,00084,000

Jan 1990

109,199,000363,000

Feb 1990

109,435,000236,000

Mar 1990

109,644,000209,000

Apr 1990

109,686,00042,000

May 1990

109,839,000153,000

Jun 1990

109,856,00017,000

Jul 1990

109,824,000-32,000

Aug 1990

109,616,000-208,000

Sep 1990

109,518,000-98,000

Oct 1990

109,367,000-151,000

Nov 1990

109,214,000-153,000

Dec 1990

109,166,000-48,000

Jan 1991

109,055,000-111,000

Feb 1991

108,734,000-321,000

Mar 1991

108,574,000-160,000

Apr 1991

108,364,000-210,000

May 1991

108,249,000-115,000

Jun 1991

108,334,00085,000

Jul 1991

108,292,000-42,000

Aug 1991

108,310,00018,000

Sep 1991

108,336,00026,000

Oct 1991

108,357,00021,000

Nov 1991

108,296,000-61,000

Dec 1991

108,328,00032,000

Jan 1992

108,369,00041,000

Feb 1992

108,311,000-58,000

Mar 1992

108,365,00054,000

Apr 1992

108,519,000154,000

May 1992

108,649,000130,000

Jun 1992

108,715,00066,000

Jul 1992

108,793,00078,000

Aug 1992

108,925,000132,000

Sep 1992

108,959,00034,000

Oct 1992

109,139,000180,000

Nov 1992

109,272,000133,000

Dec 1992

109,495,000223,000

Jan 1993

109,794,000299,000

Feb 1993

110,044,000250,000

Mar 1993

109,994,000-50,000

Apr 1993

110,296,000302,000

May 1993

110,568,000272,000

Jun 1993

110,749,000181,000

Jul 1993

111,055,000306,000

Aug 1993

111,206,000151,000

Sep 1993

111,448,000242,000

Oct 1993

111,733,000285,000

Nov 1993

111,984,000251,000

Dec 1993

112,314,000330,000

Jan 1994

112,595,000281,000

Feb 1994

112,781,000186,000

Mar 1994

113,242,000461,000

Apr 1994

113,586,000344,000

May 1994

113,921,000335,000

Jun 1994

114,238,000317,000

Jul 1994

114,610,000372,000

Aug 1994

114,896,000286,000

Sep 1994

115,247,000351,000

Oct 1994

115,458,000211,000

Nov 1994

115,869,000411,000

Dec 1994

116,165,000296,000

Jan 1995

116,501,000336,000

Feb 1995

116,697,000196,000

Mar 1995

116,907,000210,000

Apr 1995

117,069,000162,000

May 1995

117,049,000-20,000

Jun 1995

117,286,000237,000

Jul 1995

117,380,00094,000

Aug 1995

117,634,000254,000

Sep 1995

117,875,000241,000

Oct 1995

118,031,000156,000

Nov 1995

118,175,000144,000

Dec 1995

118,320,000145,000

Jan 1996

118,316,000-4,000

Feb 1996

118,739,000423,000

Mar 1996

118,993,000254,000

Apr 1996

119,158,000165,000

May 1996

119,486,000328,000

Jun 1996

119,769,000283,000

Jul 1996

120,015,000246,000

Aug 1996

120,199,000184,000

Sep 1996

120,410,000211,000

Oct 1996

120,665,000255,000

Nov 1996

120,961,000296,000

Dec 1996

121,143,000182,000

Jan 1997

121,363,000220,000

Feb 1997

121,675,000312,000

Mar 1997

121,990,000315,000

Apr 1997

122,286,000296,000

May 1997

122,546,000260,000

Jun 1997

122,814,000268,000

Jul 1997

123,111,000297,000

Aug 1997

123,093,000-18,000

Sep 1997

123,585,000492,000

Oct 1997

123,929,000344,000

Nov 1997

124,235,000306,000

Dec 1997

124,549,000314,000

Jan 1998

124,812,000263,000

Feb 1998

125,016,000204,000

Mar 1998

125,164,000148,000

Apr 1998

125,442,000278,000

May 1998

125,844,000402,000

Jun 1998

126,076,000232,000

Jul 1998

126,205,000129,000

Aug 1998

126,544,000339,000

Sep 1998

126,752,000208,000

Oct 1998

126,954,000202,000

Nov 1998

127,231,000277,000

Dec 1998

127,596,000365,000

Jan 1999

127,702,000106,000

Feb 1999

128,120,000418,000

Mar 1999

128,227,000107,000

Apr 1999

128,597,000370,000

May 1999

128,808,000211,000

Jun 1999

129,089,000281,000

Jul 1999

129,414,000325,000

Aug 1999

129,569,000155,000

Sep 1999

129,772,000203,000

Oct 1999

130,177,000405,000

Nov 1999

130,466,000289,000

Dec 1999

130,772,000306,000

Jan 2000

131,005,000233,000

Feb 2000

131,124,000119,000

Mar 2000

131,596,000472,000

Apr 2000

131,888,000292,000

May 2000

132,105,000217,000

Jun 2000

132,061,000-44,000

Jul 2000

132,236,000175,000

Aug 2000

132,230,000-6,000

Sep 2000

132,353,000123,000

Oct 2000

132,351,000-2,000

Nov 2000

132,556,000205,000

Dec 2000

132,709,000153,000

Jan 2001

132,698,000-11,000

Feb 2001

132,789,00091,000

Mar 2001

132,747,000-42,000

Apr 2001

132,463,000-284,000

May 2001

132,410,000-53,000

Jun 2001

132,299,000-111,000

Jul 2001

132,177,000-122,000

Aug 2001

132,028,000-149,000

Sep 2001

131,771,000-257,000

Oct 2001

131,454,000-317,000

Nov 2001

131,142,000-312,000

Dec 2001

130,982,000-160,000

Jan 2002

130,852,000-130,000

Feb 2002

130,736,000-116,000

Mar 2002

130,717,000-19,000

Apr 2002

130,623,000-94,000

May 2002

130,634,00011,000

Jun 2002

130,684,00050,000

Jul 2002

130,590,000-94,000

Aug 2002

130,587,000-3,000

Sep 2002

130,501,000-86,000

Oct 2002

130,628,000127,000

Nov 2002

130,615,000-13,000

Dec 2002

130,472,000-143,000

Jan 2003

130,580,000108,000

Feb 2003

130,444,000-136,000

Mar 2003

130,232,000-212,000

Apr 2003

130,177,000-55,000

May 2003

130,196,00019,000

Jun 2003

130,194,000-2,000

Jul 2003

130,191,000-3,000

Aug 2003

130,149,000-42,000

Sep 2003

130,254,000105,000

Oct 2003

130,454,000200,000

Nov 2003

130,474,00020,000

Dec 2003

130,588,000114,000

Jan 2004

130,769,000181,000

Feb 2004

130,825,00056,000

Mar 2004

131,142,000317,000

Apr 2004

131,411,000269,000

May 2004

131,694,000283,000

Jun 2004

131,793,00099,000

Jul 2004

131,848,00055,000

Aug 2004

131,937,00089,000

Sep 2004

132,093,000156,000

Oct 2004

132,447,000354,000

Nov 2004

132,503,00056,000

Dec 2004

132,624,000121,000

Jan 2005

132,774,000150,000

Feb 2005

133,032,000258,000

Mar 2005

133,156,000124,000

Apr 2005

133,518,000362,000

May 2005

133,690,000172,000

Jun 2005

133,942,000252,000

Jul 2005

134,296,000354,000

Aug 2005

134,498,000202,000

Sep 2005

134,566,00068,000

Oct 2005

134,655,00089,000

Nov 2005

134,993,000338,000

Dec 2005

135,149,000156,000

Jan 2006

135,429,000280,000

Feb 2006

135,737,000308,000

Mar 2006

136,047,000310,000

Apr 2006

136,205,000158,000

May 2006

136,244,00039,000

Jun 2006

136,325,00081,000

Jul 2006

136,520,000195,000

Aug 2006

136,694,000174,000

Sep 2006

136,843,000149,000

Oct 2006

136,852,0009,000

Nov 2006

137,063,000211,000

Dec 2006

137,249,000186,000

Jan 2007

137,477,000228,000

Feb 2007

137,558,00081,000

Mar 2007

137,793,000235,000

Apr 2007

137,842,00049,000

May 2007

137,993,000151,000

Jun 2007

138,069,00076,000

Jul 2007

138,038,000-31,000

Aug 2007

138,015,000-23,000

Sep 2007

138,095,00080,000

Oct 2007

138,174,00079,000

Nov 2007

138,284,000110,000

Dec 2007

138,392,000108,000

Jan 2008

138,403,00011,000

Feb 2008

138,324,000-79,000

Mar 2008

138,275,000-49,000

Apr 2008

138,035,000-240,000

May 2008

137,858,000-177,000

Jun 2008

137,687,000-171,000

Jul 2008

137,491,000-196,000

Aug 2008

137,213,000-278,000

Sep 2008

136,753,000-460,000

Oct 2008

136,272,000-481,000

Nov 2008

135,545,000-727,000

Dec 2008

134,839,000-706,000

Jan 2009

134,055,000-784,000

Feb 2009

133,312,000-743,000

Mar 2009

132,512,000-800,000

Apr 2009

131,817,000-695,000

May 2009

131,475,000-342,000

Jun 2009

131,008,000-467,000

Jul 2009

130,668,000-340,000

Aug 2009

130,485,000-183,000

Sep 2009

130,244,000-241,000

Oct 2009

130,045,000-199,000

Nov 2009

130,057,00012,000

Dec 2009

129,788,000-269,000

Jan 2010

129,790,0002,000

Feb 2010

129,698,000-92,000

Mar 2010

129,879,000181,000

Apr 2010

130,110,000231,000

May 2010

130,650,000540,000

Jun 2010

130,511,000-139,000

Jul 2010

130,427,000-84,000

Aug 2010

130,422,000-5,000

Sep 2010

130,357,000-65,000

Oct 2010

130,625,000268,000

Nov 2010

130,750,000125,000

Dec 2010

130,822,00072,000

Jan 2011

130,841,00019,000

Feb 2011

131,053,000212,000

Mar 2011

131,288,000235,000

Apr 2011

131,602,000314,000

May 2011

131,703,000101,000

Jun 2011

131,939,000236,000

Jul 2011

131,999,00060,000

Aug 2011

132,125,000126,000

Sep 2011

132,358,000233,000

Oct 2011

132,562,000204,000

Nov 2011

132,694,000132,000

Dec 2011

132,896,000202,000

Jan 2012

133,250,000354,000

Feb 2012

133,512,000262,000

Mar 2012

133,752,000240,000

Apr 2012

133,834,00082,000

May 2012

133,934,000100,000

Jun 2012

134,007,00073,000

Jul 2012

134,159,000152,000

Aug 2012

134,331,000172,000

Sep 2012

134,518,000187,000

Oct 2012

134,677,000159,000

Nov 2012

134,833,000156,000

Dec 2012

135,072,000239,000

Jan 2013

135,263,000191,000

Feb 2013

135,541,000278,000

Mar 2013

135,680,000139,000

Apr 2013

135,871,000191,000

May 2013

136,093,000222,000

Jun 2013

136,274,000181,000

Jul 2013

136,386,000112,000

Aug 2013

136,628,000242,000

Sep 2013

136,815,000187,000

Oct 2013

137,040,000225,000

Nov 2013

137,304,000264,000

Dec 2013

137,373,00069,000

Jan 2014

137,548,000175,000

Feb 2014

137,714,000166,000

Mar 2014

137,968,000254,000

Apr 2014

138,293,000325,000

May 2014

138,511,000218,000

Jun 2014

138,837,000326,000

Jul 2014

139,069,000232,000

Aug 2014

139,257,000188,000

Sep 2014

139,566,000309,000

Oct 2014

139,818,000252,000

Nov 2014

140,109,000291,000

Dec 2014

140,377,000268,000

Jan 2015

140,568,000191,000

Feb 2015

140,839,000271,000

Mar 2015

140,910,00071,000

Apr 2015

141,194,000284,000

May 2015

141,525,000331,000

Jun 2015

141,699,000174,000

Jul 2015

142,001,000302,000

Aug 2015

142,126,000125,000

Sep 2015

142,281,000155,000

Oct 2015

142,587,000306,000

Nov 2015

142,824,000237,000

Dec 2015

143,097,000273,000

Jan 2016

143,205,000108,000

Feb 2016

143,417,000212,000

Mar 2016

143,654,000237,000

Apr 2016

143,851,000197,000

May 2016

143,892,00041,000

Jun 2016

144,150,000258,000

Jul 2016

144,521,000371,000

Aug 2016

144,664,000143,000

Sep 2016

144,953,000289,000

Oct 2016

145,071,000118,000

Nov 2016

145,201,000130,000

Dec 2016

145,415,000214,000

Jan 2017

145,612,000197,000

Feb 2017

145,795,000183,000

Mar 2017

145,934,000139,000

Apr 2017

146,154,000220,000

May 2017

146,295,000141,000

Jun 2017

146,506,000211,000

Jul 2017

146,734,000228,000

Aug 2017

146,924,000190,000

Sep 2017

146,966,00042,000

Oct 2017

147,215,000249,000

Nov 2017

147,411,000196,000

Dec 2017

147,590,000179,000

Jan 2018

147,671,00081,000

Feb 2018

148,049,000378,000

Mar 2018

148,244,000195,000

Apr 2018

148,397,000153,000

May 2018

148,667,000270,000

Jun 2018

148,881,000214,000

Jul 2018

149,030,000149,000

Aug 2018

149,259,000229,000

Sep 2018

149,364,000105,000

Oct 2018

149,576,000212,000

Nov 2018

149,668,00092,000

Dec 2018

149,908,000240,000

Jan 2019

150,145,000237,000

Feb 2019

150,095,000-50,000

Mar 2019

150,263,000168,000

Apr 2019

150,482,000219,000

May 2019

150,545,00063,000

Jun 2019

150,720,000175,000

Jul 2019

150,913,000193,000

Aug 2019

151,108,000195,000

Sep 2019

151,329,000221,000

Oct 2019

151,524,000195,000

Nov 2019

151,758,000234,000

Dec 2019

151,919,000161,000

Jan 2020

152,234,000315,000

Feb 2020

152,523,000289,000

Mar 2020

150,840,000-1,683,000

Apr 2020

130,161,000-20,679,000

May 2020

132,994,0002,833,000

Jun 2020

137,840,0004,846,000

Jul 2020

139,566,0001,726,000

Aug 2020

141,149,0001,583,000

Sep 2020

141,865,000716,000

Oct 2020

142,545,000680,000

Nov 2020

142,809,000264,000

Dec 2020

142,582,000-227,000
Unemployment rates for selected groups, February, April, and December 2020
Race and Hispanic or Latino ethnicityFebruary 2020April 2020December 2020

Total, 16 years and older

3.514.86.7

White

3.014.16.0

Black or African American

6.016.79.9

Asian

2.414.55.9

Hispanic or Latino

4.418.99.3
Percent change in consumer prices for selected items in April 2020, seasonally adjusted
Expenditure categoryPercent change

Car and truck rental (1998)

-16.6

Airline fares (1989)

-15.2

Hotel and motel lodging (1967)

-8.1

Women’s footwear (1978)

-5.2

Full service meals and snacks (1998)

-0.3

Carbonated drinks (1978)

4.5

Household paper products (1997)

4.5

Cookies (1978)

5.1

Chicken (2004)

5.8

Increasing Access and Opportunity: Using Quality Data to Inform Evidence-Based Policy

We have a guest blogger for this edition of Commissioner’s Corner. Savi Swick is a Supervisory Research Analyst in the U.S. Department of Labor’s Office of Disability Employment Policy.

Symbols representing different types of disabilities

During National Disability Employment Awareness Month each October, there is much to celebrate and reflect upon. It’s a time to reaffirm our commitment to increasing access and opportunity for workers with disabilities and honor the value and talent they add to America’s workforce and economy. And this year’s celebration is doubly essential, marking both 75 years of this observance and helping bring to a close the yearlong commemoration of the 30th anniversary of the Americans with Disabilities Act.

For researchers like me, it’s also an opportunity to celebrate the importance of data. As a research analyst in the U.S. Department of Labor’s Office of Disability Employment Policy, my thoughts turn to how credible, consistent data are key to delivering on the promise of disability inclusion inherent in the Americans with Disabilities Act, today and into the future.

That’s why we partnered with BLS in 2008 to add six disability-related questions to the monthly Current Population Survey, the official source for estimates on U.S. labor force participation, employment, and unemployment. As a result, monthly data on the employment status of people with disabilities were released for the first time in January 2009—and have been every month since.

In addition, we collaborated with BLS and the U.S. Department of Labor’s Chief Evaluation Office to gather additional data through supplements to the Current Population Survey in May 2012 and July 2019. Through these supplements, we gleaned critical information on barriers to employment, prior work experience, career and financial assistance, requested changes to the workplace, and other related topics from respondents with disabilities.

Today, these data provide reliable, accurate information to a range of stakeholders on a topic of critical importance to America’s families and communities. Most significantly, they help facilitate evidence-based policymaking at the national, state, and local levels.

What exactly is evidence-based policymaking? It’s the simple notion that public policy should be informed by established, objective evidence. While that may seem obvious in principle, the reality is that, absent such evidence, policymakers often make decisions based on assumptions derived from anecdotal evidence, which can be subjective. This can lead to inefficient use of public resources and poor outcomes.

That’s because—and this is what often fascinates data geeks like me—things are not always as they seem. Often, data reveal that what we assume to be true, in fact, may not be true, or at least not the whole truth. This is especially the case for complex, multifaceted issues, such as the employment of people with disabilities.

Increasing access and opportunity requires us to first understand what the barriers to access are and where the opportunities exist. It also requires us to anticipate changes and identify intersections. For example, data from May 2012 and July 2019 supplements pinpointed a lack of transportation as an ongoing barrier to work for many people with disabilities. As a result, the Office of Disability Employment Policy, in partnership with the U.S. Department of Transportation and the U.S. Access Board, is engaging disability advocates and private industry to promote more accessible transportation options—especially inclusive autonomous vehicles that can help people with disabilities get to work.

Of course, the employment landscape has shifted this year due to the COVID-19 pandemic. The changes it has brought to our workforce and economy compel us to consider what questions we need to ask now to ensure we can meet the needs of workers with disabilities in the years ahead. Already, BLS data are helping us detect trends, especially in the context of different occupations.

In any climate—whether the historically robust economy before the pandemic or one recovering in the wake of unprecedented challenges—quality data helps us serve America’s 15 million working-age people with disabilities better. They also help us deliver on the spirit of the bipartisan 2018 Foundations for Evidence-Based Policymaking Act. Going forward, with continued support from BLS, the Chief Evaluation Office, and Department of Labor’s Chief Data Officer, we will continue to develop and implement data-driven policies and programs that meet the needs of America’s workers with disabilities, every month of every year.

New Measures of How Widespread Employment Changes Are across States and Metro Areas

BLS recently began publishing a new set of measures on employment changes in states and metropolitan areas. For decades we have published monthly estimates of employment, hours, and earnings for each state and metro area. Our new measure summarizes how widespread employment increases or decreases are across all states or metro areas. We call this measure a diffusion index.

What’s a diffusion index? Let me explain how we create the measure.

Let’s say we’re creating a diffusion index for the 50 states and the District of Columbia. We start by assigning each state and D.C. a value depending on whether its employment decreased, stayed the same, or increased over the period we’re looking at.

  • The assigned value is 0 if employment decreased.
  • The assigned value is 50 if employment stayed the same.
  • The assigned value is 100 if employment increased.

The diffusion index is the average of those 51 values. To create a diffusion index for metro areas, we assign values of 0, 50, or 100 for each of 388 metro areas and then average those values. We calculate diffusion indexes for employment changes over 1 month, 3 months, 6 months, and 12 months.

Now that we understand the simple arithmetic for calculating diffusion indexes, what do they mean? An index greater than 50 means more states or metro areas had increasing employment over the period. An index below 50 means more states or metro areas had decreasing employment. At the extremes, an index of 0 means employment fell in all states or metro areas; an index of 100 means employment rose in all of them. A diffusion index of 50 doesn’t necessarily mean 50 percent of the states or areas had increasing employment and the other 50 percent had decreasing employment. It just means the same number of states or areas had increases and decreases, with any of the other states or areas having no change.

The chart below shows 3-month diffusion indexes for all states and metro areas. You can see how all states and nearly all metro areas had job losses during the worst of the 2007–09 recession. We see it again more recently with the downturn associated with the COVID-19 pandemic.

3-month diffusion indexes for all states and all metropolitan areas, 2007–20

Editor’s note: Data for this chart are available in the table below.

Diffusion indexes aren’t a new analytical tool. We publish other diffusion indexes using national employment data that summarize how employment change is dispersed across industries. The Federal Reserve Bank of Philadelphia publishes diffusion indexes using a variety of data. The new BLS diffusion indexes summarize how employment is changing across geographic areas to give us another perspective of the labor market.

Keep a look out for the new data. We update the indexes each month in our public database.

3-month diffusion indexes for all states and all metropolitan areas
MonthAll statesAll metropolitan areas

Jan 2007

96.177.7

Feb 2007

84.372.2

Mar 2007

84.372.6

Apr 2007

74.559.1

May 2007

86.365.3

Jun 2007

69.661.2

Jul 2007

78.467.7

Aug 2007

74.561.2

Sep 2007

56.951.3

Oct 2007

62.753.2

Nov 2007

79.459.1

Dec 2007

80.463.0

Jan 2008

81.465.3

Feb 2008

78.464.0

Mar 2008

52.050.6

Apr 2008

41.236.2

May 2008

25.529.8

Jun 2008

23.535.4

Jul 2008

16.733.9

Aug 2008

16.729.8

Sep 2008

15.723.6

Oct 2008

7.817.8

Nov 2008

7.811.9

Dec 2008

3.910.1

Jan 2009

2.04.3

Feb 2009

2.03.9

Mar 2009

0.04.1

Apr 2009

0.03.6

May 2009

2.04.9

Jun 2009

3.911.7

Jul 2009

8.814.6

Aug 2009

4.914.0

Sep 2009

5.920.0

Oct 2009

16.728.0

Nov 2009

21.638.5

Dec 2009

19.638.1

Jan 2010

26.538.8

Feb 2010

18.636.0

Mar 2010

70.656.3

Apr 2010

94.174.6

May 2010

100.086.6

Jun 2010

98.079.0

Jul 2010

85.364.3

Aug 2010

35.342.4

Sep 2010

39.244.7

Oct 2010

70.663.7

Nov 2010

74.564.8

Dec 2010

88.273.7

Jan 2011

62.757.0

Feb 2011

76.561.9

Mar 2011

87.367.9

Apr 2011

98.075.5

May 2011

90.267.0

Jun 2011

80.456.4

Jul 2011

83.366.8

Aug 2011

82.472.3

Sep 2011

98.081.8

Oct 2011

82.464.8

Nov 2011

96.166.8

Dec 2011

82.463.1

Jan 2012

88.276.7

Feb 2012

97.178.9

Mar 2012

98.083.1

Apr 2012

96.175.9

May 2012

94.170.0

Jun 2012

70.658.1

Jul 2012

74.557.0

Aug 2012

77.564.4

Sep 2012

86.367.5

Oct 2012

97.176.7

Nov 2012

93.175.4

Dec 2012

90.273.7

Jan 2013

88.270.2

Feb 2013

94.179.5

Mar 2013

99.075.9

Apr 2013

87.375.0

May 2013

82.468.7

Jun 2013

82.468.4

Jul 2013

81.470.6

Aug 2013

94.176.4

Sep 2013

92.277.8

Oct 2013

90.277.8

Nov 2013

94.174.7

Dec 2013

81.473.2

Jan 2014

88.268.7

Feb 2014

80.466.5

Mar 2014

86.373.6

Apr 2014

96.182.0

May 2014

98.083.4

Jun 2014

96.183.5

Jul 2014

96.174.2

Aug 2014

92.274.5

Sep 2014

90.277.2

Oct 2014

98.079.9

Nov 2014

96.179.8

Dec 2014

98.081.8

Jan 2015

93.180.0

Feb 2015

84.374.5

Mar 2015

64.762.5

Apr 2015

74.565.1

May 2015

84.377.1

Jun 2015

84.378.2

Jul 2015

92.284.1

Aug 2015

80.474.5

Sep 2015

86.374.1

Oct 2015

88.275.9

Nov 2015

88.274.6

Dec 2015

88.273.2

Jan 2016

75.571.1

Feb 2016

81.472.4

Mar 2016

78.469.5

Apr 2016

86.377.1

May 2016

72.567.3

Jun 2016

55.957.7

Jul 2016

84.371.3

Aug 2016

86.376.2

Sep 2016

94.185.1

Oct 2016

68.666.9

Nov 2016

82.473.6

Dec 2016

78.464.7

Jan 2017

84.370.0

Feb 2017

79.468.9

Mar 2017

98.076.5

Apr 2017

88.272.0

May 2017

78.468.4

Jun 2017

91.269.6

Jul 2017

80.471.6

Aug 2017

91.275.6

Sep 2017

76.560.8

Oct 2017

80.473.8

Nov 2017

84.370.7

Dec 2017

91.273.8

Jan 2018

90.274.2

Feb 2018

96.180.2

Mar 2018

96.180.9

Apr 2018

86.372.9

May 2018

82.473.6

Jun 2018

94.176.7

Jul 2018

91.281.3

Aug 2018

94.177.2

Sep 2018

82.468.4

Oct 2018

94.172.8

Nov 2018

92.272.3

Dec 2018

88.267.9

Jan 2019

89.279.4

Feb 2019

84.373.3

Mar 2019

82.474.9

Apr 2019

61.856.4

May 2019

64.758.5

Jun 2019

66.755.4

Jul 2019

74.560.8

Aug 2019

80.467.1

Sep 2019

79.466.4

Oct 2019

70.660.3

Nov 2019

68.663.7

Dec 2019

74.567.9

Jan 2020

87.375.9

Feb 2020

86.371.8

Mar 2020

5.929.0

Apr 2020

0.00.0

May 2020

0.00.3

Jun 2020[p]

0.00.6

[p] preliminary

New State and Metropolitan Area Data from the Job Openings and Labor Turnover Survey

Soon after I became Commissioner, the top-notch BLS staff shared with me their vision to expand the Job Openings and Labor Turnover Survey (JOLTS). The JOLTS program publishes data each month on the number and rate of job openings, hires, and separations (broken out by quits, layoffs and discharges, and other separations). These data are available at the national level and for the four large geographic regions—Northeast, Midwest, South, and West.

That left a major data gap on labor demand, hires, and separations for states and metropolitan areas. BLS provides data on labor supply for states and metro areas each month from the Local Area Unemployment Statistics program. We also provide data on employment change in states and metro areas each month from the Current Employment Statistics survey. Employment change is the net effect of hires and separations, but it doesn’t show the underlying flow of job creation and destruction. Having better, timelier state and metro JOLTS data would provide a quicker signal about whether labor demand is accelerating or weakening in local economies.

About 2 months after the staff briefed me, the JOLTS program published experimental state estimates for the first time on May 24, 2019. We have been updating those estimates on a quarterly basis since then. We use a statistical model to help us produce the most current state estimates. We then improve those estimates during an annual benchmark process by taking advantage of data available from the Quarterly Census of Employment and Wages. The JOLTS program is well on its way to moving these state estimates into its official, monthly data stream. Look for that to happen in the second half of 2021!

The President’s proposed budget for fiscal year 2021 includes three improvements to the JOLTS program.

  • Expand the sample to support direct sample-based estimates for each state.
  • Accelerate the review and publication of the estimates.
  • Add questions to provide more information about job openings, hires, and separations.

If funded, this proposal would allow BLS to improve the data quality available from the current JOLTS state estimates. It also would let us add very broad industry detail for each state and more industry detail at the national level.

The proposed larger sample size may also let us produce model-assisted JOLTS estimates for many metro areas. To demonstrate this potential, the JOLTS team produced a one-time set of research estimates for the 18 largest metropolitan statistical areas, those with 1.5 million or more employees. These research estimates show the potential for data that would be available regularly with a larger JOLTS sample. I encourage you to explore this exciting new research series and let us know what you think.

Number of unemployed per job opening in the United States and four large metropolitan areas, 2007–19

Editor’s note: Data for this chart are available in the table below.

This is just one example of the excellent work I see at BLS every day. The BLS staff are consummate professionals who continue to do outstanding work even in the most trying of times. The entire BLS staff has been teleworking now for several months due to COVID-19, and every program continues to produce high quality data on schedule! Even in these extraordinary circumstances, BLS professionals continue to innovate and find ways to improve quality and develop new gold standard data products to help the policymakers, businesses, and the public make better-informed decisions.

Number of unemployed per job opening in the United States and four large metropolitan areas
DateNew York-Newark-Jersey City, NY-NJ-PADallas-Fort Worth-Arlington, TXChicago-Naperville-Elgin, IL-IN-WILos Angeles-Long Beach-Anaheim, CAUnited States

Jan 2007

1.81.41.81.61.6

Feb 2007

1.81.41.91.61.6

Mar 2007

1.71.31.81.61.6

Apr 2007

1.61.11.61.51.4

May 2007

1.51.01.51.51.4

Jun 2007

1.51.11.61.41.4

Jul 2007

1.61.21.81.51.5

Aug 2007

1.71.21.91.51.5

Sep 2007

1.71.21.81.71.5

Oct 2007

1.61.11.71.81.5

Nov 2007

1.61.21.81.91.5

Dec 2007

1.71.21.91.91.6

Jan 2008

1.91.32.02.11.7

Feb 2008

2.11.32.22.21.8

Mar 2008

2.21.32.42.21.9

Apr 2008

2.11.22.22.01.8

May 2008

2.01.22.22.11.8

Jun 2008

1.91.22.42.51.9

Jul 2008

2.21.43.03.02.2

Aug 2008

2.31.73.13.52.4

Sep 2008

2.41.83.13.62.5

Oct 2008

2.51.93.04.02.6

Nov 2008

2.82.13.44.62.9

Dec 2008

3.12.43.95.93.3

Jan 2009

3.62.94.86.74.0

Feb 2009

4.43.25.57.34.6

Mar 2009

5.03.56.47.45.1

Apr 2009

5.03.66.77.35.3

May 2009

5.14.06.87.15.4

Jun 2009

5.14.67.26.85.6

Jul 2009

5.25.37.77.46.0

Aug 2009

5.15.67.97.76.2

Sep 2009

5.45.88.08.06.1

Oct 2009

5.95.37.87.85.8

Nov 2009

6.75.68.68.25.9

Dec 2009

7.15.69.58.36.2

Jan 2010

7.06.310.88.36.2

Feb 2010

7.06.410.37.56.2

Mar 2010

7.05.98.87.15.9

Apr 2010

6.55.17.86.75.4

May 2010

5.94.86.66.54.9

Jun 2010

5.05.16.26.74.8

Jul 2010

4.85.26.07.14.9

Aug 2010

4.75.46.27.54.9

Sep 2010

4.94.76.17.54.7

Oct 2010

4.64.25.27.14.5

Nov 2010

4.84.05.07.14.5

Dec 2010

5.34.15.17.14.6

Jan 2011

6.04.35.57.15.0

Feb 2011

6.14.25.76.84.9

Mar 2011

5.54.05.36.34.6

Apr 2011

5.03.85.15.84.2

May 2011

4.63.64.65.84.1

Jun 2011

4.53.74.55.64.0

Jul 2011

4.63.84.65.94.1

Aug 2011

4.53.84.96.04.0

Sep 2011

4.43.44.65.83.8

Oct 2011

4.23.14.25.63.6

Nov 2011

4.03.04.25.33.6

Dec 2011

4.23.04.85.53.7

Jan 2012

4.63.05.25.93.7

Feb 2012

5.33.04.86.23.7

Mar 2012

5.12.84.25.73.5

Apr 2012

4.22.43.65.03.3

May 2012

3.92.13.44.83.1

Jun 2012

3.92.13.64.63.1

Jul 2012

4.22.33.95.33.3

Aug 2012

4.02.43.95.23.4

Sep 2012

3.82.43.55.53.2

Oct 2012

3.72.13.25.03.0

Nov 2012

3.92.03.44.83.0

Dec 2012

4.02.03.75.13.2

Jan 2013

4.22.24.35.43.4

Feb 2013

4.22.14.15.43.4

Mar 2013

4.02.03.94.93.2

Apr 2013

3.51.93.54.12.9

May 2013

3.21.93.53.82.7

Jun 2013

3.22.13.63.62.7

Jul 2013

3.42.33.83.82.9

Aug 2013

3.42.33.73.92.9

Sep 2013

3.42.13.64.02.8

Oct 2013

3.22.03.33.92.5

Nov 2013

3.22.03.24.12.5

Dec 2013

3.22.03.34.22.6

Jan 2014

3.42.03.54.22.7

Feb 2014

3.41.93.53.72.7

Mar 2014

3.21.93.33.32.6

Apr 2014

2.81.72.62.82.2

May 2014

2.51.62.12.82.0

Jun 2014

2.41.62.02.81.9

Jul 2014

2.61.62.13.12.0

Aug 2014

2.61.62.12.91.9

Sep 2014

2.51.62.02.91.9

Oct 2014

2.31.51.92.71.7

Nov 2014

2.41.51.92.91.8

Dec 2014

2.51.31.92.91.8

Jan 2015

2.61.32.02.91.9

Feb 2015

2.51.31.92.61.8

Mar 2015

2.41.31.82.41.7

Apr 2015

2.21.21.62.21.6

May 2015

2.01.11.52.21.5

Jun 2015

1.91.01.62.31.5

Jul 2015

1.91.01.62.31.5

Aug 2015

1.90.91.62.31.5

Sep 2015

1.80.91.52.31.4

Oct 2015

1.70.81.52.01.3

Nov 2015

1.60.81.52.01.3

Dec 2015

1.60.81.51.91.4

Jan 2016

1.70.91.61.91.4

Feb 2016

1.80.81.61.71.5

Mar 2016

1.70.81.61.61.4

Apr 2016

1.60.71.61.61.3

May 2016

1.40.71.41.61.2

Jun 2016

1.40.81.41.61.3

Jul 2016

1.40.91.41.81.3

Aug 2016

1.50.91.51.91.4

Sep 2016

1.40.91.51.91.3

Oct 2016

1.30.91.51.71.3

Nov 2016

1.30.91.41.71.3

Dec 2016

1.30.91.51.71.3

Jan 2017

1.41.01.71.81.4

Feb 2017

1.51.01.71.81.4

Mar 2017

1.51.01.51.81.4

Apr 2017

1.30.91.41.61.2

May 2017

1.30.91.21.51.1

Jun 2017

1.31.01.21.41.1

Jul 2017

1.31.11.21.51.1

Aug 2017

1.41.11.21.61.1

Sep 2017

1.41.01.11.51.1

Oct 2017

1.31.01.01.31.0

Nov 2017

1.21.01.01.31.0

Dec 2017

1.21.01.11.31.0

Jan 2018

1.21.11.31.31.1

Feb 2018

1.21.11.31.21.1

Mar 2018

1.21.11.21.21.1

Apr 2018

1.11.01.11.11.0

May 2018

1.01.00.91.00.9

Jun 2018

1.00.90.81.10.9

Jul 2018

1.00.80.81.10.9

Aug 2018

1.00.80.91.20.9

Sep 2018

0.90.80.91.20.8

Oct 2018

0.90.80.81.10.8

Nov 2018

0.80.80.81.20.8

Dec 2018

0.90.70.81.30.8

Jan 2019

1.00.80.91.40.9

Feb 2019

1.10.81.01.40.9

Mar 2019

1.10.80.91.40.9

Apr 2019

1.00.70.91.10.8

May 2019

0.80.70.81.00.8

Jun 2019

0.80.60.80.90.8

Jul 2019

0.80.70.81.00.8

Aug 2019

0.80.80.91.10.9

Sep 2019

0.80.80.91.20.8

Oct 2019

0.80.80.81.10.8

Nov 2019

0.80.80.71.00.8

Dec 2019

0.80.80.71.00.8