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United States Retail Inventories Ex Autos

Price

0.5 %

Change +/-

-0.1 %

Percentage Change

-18.18 %

The current value of the Retail Inventories Ex Autos in United States is 0.5 %. The Retail Inventories Ex Autos in United States decreased to 0.5 % on 8/1/2024, after it was 0.6 % on 7/1/2024. From 2/1/1992 to 9/1/2024, the average GDP in United States was 0.29 %. The all-time high was reached on 12/1/2021 with 3.8 %, while the lowest value was recorded on 12/1/2008 with -2.1 %.

Source: U.S. Census Bureau

Retail Inventories Ex Autos ·

3 years
5 years
10 years
25 Years
Max

Retail Inventory Excluding Autos

	Retail Inventory Excluding Autos
2/1/1992	0.6 %
3/1/1992	0.3 %
4/1/1992	1.1 %
6/1/1992	0.7 %
7/1/1992	1.1 %
9/1/1992	0.3 %
10/1/1992	0.3 %
11/1/1992	0.5 %
12/1/1992	1.2 %
1/1/1993	0.9 %
2/1/1993	0.8 %
3/1/1993	1 %
4/1/1993	0.3 %
5/1/1993	0.4 %
6/1/1993	0.2 %
7/1/1993	0.4 %
8/1/1993	0.1 %
9/1/1993	0.5 %
10/1/1993	0.2 %
11/1/1993	0.6 %
12/1/1993	0.8 %
2/1/1994	1 %
3/1/1994	0.2 %
4/1/1994	0.6 %
5/1/1994	1.4 %
6/1/1994	1.5 %
8/1/1994	0.9 %
9/1/1994	0.5 %
10/1/1994	0.7 %
11/1/1994	0.5 %
12/1/1994	0.6 %
1/1/1995	0.7 %
2/1/1995	0.5 %
3/1/1995	0.2 %
4/1/1995	0.7 %
5/1/1995	0.4 %
6/1/1995	0.5 %
8/1/1995	1.4 %
9/1/1995	0.1 %
10/1/1995	0.4 %
11/1/1995	0.6 %
2/1/1996	0.4 %
3/1/1996	0.1 %
4/1/1996	0.5 %
5/1/1996	0.2 %
7/1/1996	0.9 %
8/1/1996	0.3 %
10/1/1996	1 %
11/1/1996	0.1 %
2/1/1997	0.6 %
4/1/1997	0.7 %
5/1/1997	0.6 %
6/1/1997	0.2 %
7/1/1997	0.4 %
9/1/1997	1 %
11/1/1997	0.1 %
12/1/1997	0.4 %
1/1/1998	0.5 %
2/1/1998	0.5 %
3/1/1998	0.9 %
4/1/1998	0.4 %
6/1/1998	1.2 %
7/1/1998	0.6 %
8/1/1998	0.2 %
9/1/1998	0.2 %
11/1/1998	0.5 %
12/1/1998	0.4 %
1/1/1999	0.5 %
2/1/1999	0.1 %
3/1/1999	0.4 %
4/1/1999	0.5 %
5/1/1999	0.1 %
6/1/1999	0.5 %
7/1/1999	0.1 %
8/1/1999	0.4 %
9/1/1999	0.5 %
10/1/1999	0.4 %
11/1/1999	0.8 %
12/1/1999	1.1 %
2/1/2000	0.5 %
3/1/2000	0.4 %
5/1/2000	0.9 %
6/1/2000	0.3 %
8/1/2000	0.7 %
10/1/2000	0.7 %
11/1/2000	0.5 %
12/1/2000	0.1 %
1/1/2001	0.1 %
3/1/2001	0.1 %
8/1/2001	0.6 %
10/1/2001	0.1 %
4/1/2002	0.1 %
5/1/2002	0.4 %
6/1/2002	0.1 %
7/1/2002	0.7 %
8/1/2002	0.1 %
9/1/2002	0.7 %
11/1/2002	0.2 %
12/1/2002	0.4 %
2/1/2003	0.4 %
3/1/2003	0.3 %
6/1/2003	0.1 %
7/1/2003	0.6 %
9/1/2003	0.9 %
10/1/2003	0.3 %
11/1/2003	0.4 %
2/1/2004	0.4 %
3/1/2004	0.9 %
4/1/2004	0.7 %
5/1/2004	0.6 %
6/1/2004	0.5 %
7/1/2004	0.2 %
8/1/2004	0.7 %
9/1/2004	0.3 %
10/1/2004	0.6 %
11/1/2004	1.1 %
12/1/2004	0.9 %
1/1/2005	0.7 %
2/1/2005	0.4 %
3/1/2005	0.5 %
4/1/2005	0.1 %
5/1/2005	0.4 %
6/1/2005	0.4 %
8/1/2005	0.7 %
9/1/2005	0.2 %
11/1/2005	0.5 %
12/1/2005	0.6 %
1/1/2006	0.6 %
3/1/2006	1 %
5/1/2006	0.7 %
6/1/2006	0.4 %
7/1/2006	0.1 %
8/1/2006	0.9 %
10/1/2006	0.2 %
11/1/2006	0.5 %
12/1/2006	0.3 %
1/1/2007	0.2 %
2/1/2007	0.8 %
4/1/2007	0.3 %
5/1/2007	0.8 %
6/1/2007	0.2 %
8/1/2007	0.3 %
10/1/2007	0.7 %
12/1/2007	0.7 %
1/1/2008	0.2 %
4/1/2008	0.4 %
7/1/2008	0.4 %
10/1/2009	0.2 %
1/1/2010	0.1 %
3/1/2010	0.7 %
4/1/2010	0.5 %
5/1/2010	0.3 %
6/1/2010	0.2 %
7/1/2010	0.3 %
8/1/2010	0.3 %
9/1/2010	0.4 %
10/1/2010	0.2 %
11/1/2010	0.3 %
12/1/2010	0.4 %
1/1/2011	0.5 %
3/1/2011	1.2 %
4/1/2011	0.3 %
5/1/2011	0.3 %
6/1/2011	0.2 %
8/1/2011	0.6 %
10/1/2011	0.3 %
11/1/2011	0.3 %
12/1/2011	0.1 %
2/1/2012	0.4 %
3/1/2012	0.2 %
4/1/2012	0.3 %
5/1/2012	0.7 %
6/1/2012	0.2 %
7/1/2012	0.4 %
8/1/2012	0.2 %
9/1/2012	0.1 %
10/1/2012	0.4 %
12/1/2012	0.5 %
1/1/2013	1.1 %
2/1/2013	0.3 %
4/1/2013	0.4 %
5/1/2013	0.2 %
6/1/2013	0.2 %
7/1/2013	0.6 %
8/1/2013	0.4 %
9/1/2013	0.5 %
10/1/2013	0.1 %
11/1/2013	0.8 %
12/1/2013	0.3 %
1/1/2014	0.4 %
2/1/2014	0.2 %
3/1/2014	0.5 %
5/1/2014	0.2 %
6/1/2014	0.2 %
7/1/2014	0.5 %
8/1/2014	0.2 %
10/1/2014	0.3 %
11/1/2014	0.1 %
2/1/2015	0.6 %
4/1/2015	0.7 %
6/1/2015	0.4 %
7/1/2015	0.3 %
8/1/2015	0.6 %
9/1/2015	0.7 %
10/1/2015	0.4 %
11/1/2015	0.2 %
1/1/2016	0.4 %
2/1/2016	0.1 %
3/1/2016	0.2 %
5/1/2016	0.4 %
7/1/2016	0.1 %
9/1/2016	0.3 %
11/1/2016	0.4 %
12/1/2016	0.2 %
3/1/2017	0.3 %
5/1/2017	0.1 %
6/1/2017	0.6 %
7/1/2017	0.1 %
8/1/2017	0.4 %
10/1/2017	0.4 %
11/1/2017	0.5 %
12/1/2017	0.5 %
1/1/2018	0.1 %
2/1/2018	0.1 %
4/1/2018	0.4 %
5/1/2018	0.2 %
6/1/2018	0.4 %
7/1/2018	0.2 %
8/1/2018	0.4 %
10/1/2018	0.8 %
12/1/2018	1.7 %
1/1/2019	0.5 %
2/1/2019	0.1 %
4/1/2019	0.1 %
5/1/2019	0.1 %
7/1/2019	0.2 %
10/1/2019	0.8 %
11/1/2019	0.2 %
1/1/2020	0.4 %
7/1/2020	0.5 %
8/1/2020	1 %
9/1/2020	1.4 %
10/1/2020	1.6 %
11/1/2020	0.7 %
12/1/2020	1.7 %
1/1/2021	0.8 %
2/1/2021	1.3 %
3/1/2021	0.3 %
4/1/2021	1.4 %
5/1/2021	1 %
7/1/2021	2 %
8/1/2021	0.6 %
9/1/2021	1.4 %
10/1/2021	1.5 %
11/1/2021	1.5 %
12/1/2021	3.8 %
1/1/2022	2.9 %
2/1/2022	1.5 %
3/1/2022	2.9 %
4/1/2022	1.3 %
5/1/2022	1.1 %
6/1/2022	1.3 %
7/1/2022	0.3 %
8/1/2022	0.3 %
12/1/2022	0.4 %
1/1/2023	0.2 %
3/1/2023	0.3 %
8/1/2023	0.5 %
9/1/2023	0.1 %
12/1/2023	0.5 %
1/1/2024	0.2 %
2/1/2024	0.1 %
4/1/2024	0.2 %
6/1/2024	0.3 %
7/1/2024	0.6 %
8/1/2024	0.5 %

Retail Inventories Ex Autos History

Date	Value
8/1/2024	0.5 %
7/1/2024	0.6 %
6/1/2024	0.3 %
4/1/2024	0.2 %
2/1/2024	0.1 %
1/1/2024	0.2 %
12/1/2023	0.5 %
9/1/2023	0.1 %
8/1/2023	0.5 %
3/1/2023	0.3 %
1/1/2023	0.2 %
12/1/2022	0.4 %
8/1/2022	0.3 %
7/1/2022	0.3 %
6/1/2022	1.3 %
5/1/2022	1.1 %
4/1/2022	1.3 %
3/1/2022	2.9 %
2/1/2022	1.5 %
1/1/2022	2.9 %
12/1/2021	3.8 %
11/1/2021	1.5 %
10/1/2021	1.5 %
9/1/2021	1.4 %
8/1/2021	0.6 %
7/1/2021	2 %
5/1/2021	1 %
4/1/2021	1.4 %
3/1/2021	0.3 %
2/1/2021	1.3 %
1/1/2021	0.8 %
12/1/2020	1.7 %
11/1/2020	0.7 %
10/1/2020	1.6 %
9/1/2020	1.4 %
8/1/2020	1 %
7/1/2020	0.5 %
1/1/2020	0.4 %
11/1/2019	0.2 %
10/1/2019	0.8 %
7/1/2019	0.2 %
5/1/2019	0.1 %
4/1/2019	0.1 %
2/1/2019	0.1 %
1/1/2019	0.5 %
12/1/2018	1.7 %
10/1/2018	0.8 %
8/1/2018	0.4 %
7/1/2018	0.2 %
6/1/2018	0.4 %
5/1/2018	0.2 %
4/1/2018	0.4 %
2/1/2018	0.1 %
1/1/2018	0.1 %
12/1/2017	0.5 %
11/1/2017	0.5 %
10/1/2017	0.4 %
8/1/2017	0.4 %
7/1/2017	0.1 %
6/1/2017	0.6 %
5/1/2017	0.1 %
3/1/2017	0.3 %
12/1/2016	0.2 %
11/1/2016	0.4 %
9/1/2016	0.3 %
7/1/2016	0.1 %
5/1/2016	0.4 %
3/1/2016	0.2 %
2/1/2016	0.1 %
1/1/2016	0.4 %
11/1/2015	0.2 %
10/1/2015	0.4 %
9/1/2015	0.7 %
8/1/2015	0.6 %
7/1/2015	0.3 %
6/1/2015	0.4 %
4/1/2015	0.7 %
2/1/2015	0.6 %
11/1/2014	0.1 %
10/1/2014	0.3 %
8/1/2014	0.2 %
7/1/2014	0.5 %
6/1/2014	0.2 %
5/1/2014	0.2 %
3/1/2014	0.5 %
2/1/2014	0.2 %
1/1/2014	0.4 %
12/1/2013	0.3 %
11/1/2013	0.8 %
10/1/2013	0.1 %
9/1/2013	0.5 %
8/1/2013	0.4 %
7/1/2013	0.6 %
6/1/2013	0.2 %
5/1/2013	0.2 %
4/1/2013	0.4 %
2/1/2013	0.3 %
1/1/2013	1.1 %
12/1/2012	0.5 %
10/1/2012	0.4 %
9/1/2012	0.1 %
8/1/2012	0.2 %
7/1/2012	0.4 %
6/1/2012	0.2 %
5/1/2012	0.7 %
4/1/2012	0.3 %
3/1/2012	0.2 %
2/1/2012	0.4 %
12/1/2011	0.1 %
11/1/2011	0.3 %
10/1/2011	0.3 %
8/1/2011	0.6 %
6/1/2011	0.2 %
5/1/2011	0.3 %
4/1/2011	0.3 %
3/1/2011	1.2 %
1/1/2011	0.5 %
12/1/2010	0.4 %
11/1/2010	0.3 %
10/1/2010	0.2 %
9/1/2010	0.4 %
8/1/2010	0.3 %
7/1/2010	0.3 %
6/1/2010	0.2 %
5/1/2010	0.3 %
4/1/2010	0.5 %
3/1/2010	0.7 %
1/1/2010	0.1 %
10/1/2009	0.2 %
7/1/2008	0.4 %
4/1/2008	0.4 %
1/1/2008	0.2 %
12/1/2007	0.7 %
10/1/2007	0.7 %
8/1/2007	0.3 %
6/1/2007	0.2 %
5/1/2007	0.8 %
4/1/2007	0.3 %
2/1/2007	0.8 %
1/1/2007	0.2 %
12/1/2006	0.3 %
11/1/2006	0.5 %
10/1/2006	0.2 %
8/1/2006	0.9 %
7/1/2006	0.1 %
6/1/2006	0.4 %
5/1/2006	0.7 %
3/1/2006	1 %
1/1/2006	0.6 %
12/1/2005	0.6 %
11/1/2005	0.5 %
9/1/2005	0.2 %
8/1/2005	0.7 %
6/1/2005	0.4 %
5/1/2005	0.4 %
4/1/2005	0.1 %
3/1/2005	0.5 %
2/1/2005	0.4 %
1/1/2005	0.7 %
12/1/2004	0.9 %
11/1/2004	1.1 %
10/1/2004	0.6 %
9/1/2004	0.3 %
8/1/2004	0.7 %
7/1/2004	0.2 %
6/1/2004	0.5 %
5/1/2004	0.6 %
4/1/2004	0.7 %
3/1/2004	0.9 %
2/1/2004	0.4 %
11/1/2003	0.4 %
10/1/2003	0.3 %
9/1/2003	0.9 %
7/1/2003	0.6 %
6/1/2003	0.1 %
3/1/2003	0.3 %
2/1/2003	0.4 %
12/1/2002	0.4 %
11/1/2002	0.2 %
9/1/2002	0.7 %
8/1/2002	0.1 %
7/1/2002	0.7 %
6/1/2002	0.1 %
5/1/2002	0.4 %
4/1/2002	0.1 %
10/1/2001	0.1 %
8/1/2001	0.6 %
3/1/2001	0.1 %
1/1/2001	0.1 %
12/1/2000	0.1 %
11/1/2000	0.5 %
10/1/2000	0.7 %
8/1/2000	0.7 %
6/1/2000	0.3 %
5/1/2000	0.9 %
3/1/2000	0.4 %
2/1/2000	0.5 %
12/1/1999	1.1 %
11/1/1999	0.8 %
10/1/1999	0.4 %
9/1/1999	0.5 %
8/1/1999	0.4 %
7/1/1999	0.1 %
6/1/1999	0.5 %
5/1/1999	0.1 %
4/1/1999	0.5 %
3/1/1999	0.4 %
2/1/1999	0.1 %
1/1/1999	0.5 %
12/1/1998	0.4 %
11/1/1998	0.5 %
9/1/1998	0.2 %
8/1/1998	0.2 %
7/1/1998	0.6 %
6/1/1998	1.2 %
4/1/1998	0.4 %
3/1/1998	0.9 %
2/1/1998	0.5 %
1/1/1998	0.5 %
12/1/1997	0.4 %
11/1/1997	0.1 %
9/1/1997	1 %
7/1/1997	0.4 %
6/1/1997	0.2 %
5/1/1997	0.6 %
4/1/1997	0.7 %
2/1/1997	0.6 %
11/1/1996	0.1 %
10/1/1996	1 %
8/1/1996	0.3 %
7/1/1996	0.9 %
5/1/1996	0.2 %
4/1/1996	0.5 %
3/1/1996	0.1 %
2/1/1996	0.4 %
11/1/1995	0.6 %
10/1/1995	0.4 %
9/1/1995	0.1 %
8/1/1995	1.4 %
6/1/1995	0.5 %
5/1/1995	0.4 %
4/1/1995	0.7 %
3/1/1995	0.2 %
2/1/1995	0.5 %
1/1/1995	0.7 %
12/1/1994	0.6 %
11/1/1994	0.5 %
10/1/1994	0.7 %
9/1/1994	0.5 %
8/1/1994	0.9 %
6/1/1994	1.5 %
5/1/1994	1.4 %
4/1/1994	0.6 %
3/1/1994	0.2 %
2/1/1994	1 %
12/1/1993	0.8 %
11/1/1993	0.6 %
10/1/1993	0.2 %
9/1/1993	0.5 %
8/1/1993	0.1 %
7/1/1993	0.4 %
6/1/1993	0.2 %
5/1/1993	0.4 %
4/1/1993	0.3 %
3/1/1993	1 %
2/1/1993	0.8 %
1/1/1993	0.9 %
12/1/1992	1.2 %
11/1/1992	0.5 %
10/1/1992	0.3 %
9/1/1992	0.3 %
7/1/1992	1.1 %
6/1/1992	0.7 %
4/1/1992	1.1 %
3/1/1992	0.3 %
2/1/1992	0.6 %

...

Similar Macro Indicators to Retail Inventories Ex Autos

Name	Current	Previous	Frequency
🇺🇸 Automobile production	11.18 M Units	11.73 M Units	Monthly
🇺🇸 Bankruptcies	22,060 Companies	20,316 Companies	Quarter
🇺🇸 Business Climate	48.5 points	48.7 points	Monthly
🇺🇸 Business Inventories	0.5 %	0.3 %	Monthly
🇺🇸 Capacity Utilization	78.7 %	78.2 %	Monthly
🇺🇸 CFNAI Employment Index	0 points	-0.05 points	Monthly
🇺🇸 CFNAI Index for Personal Consumption and Housing	-0.02 points	-0.02 points	Monthly
🇺🇸 CFNAI Production Index	-0.21 %	0.04 %	Monthly
🇺🇸 CFNAI Sales, Order, and Inventory Index	-0.02 %	-0.01 %	Monthly
🇺🇸 Changes in Inventory Levels	60.2 B USD	71.7 B USD	Quarter
🇺🇸 Chicago Fed National Activity Index	0.18 points	-0.26 points	Monthly
🇺🇸 Chicago PMI	41.6 points	46.6 points	Monthly
🇺🇸 Composite Leading Indicator	100.095 points	100.04 points	Monthly
🇺🇸 Composite PMI	54.1 points	54 points	Monthly
🇺🇸 Consistency Index	143.15 points	142.9 points	Monthly
🇺🇸 Corn Grain Reserves	1.76 B Bushels	4.993 B Bushels	Quarter
🇺🇸 Corporate profits	2.727 T USD	2.803 T USD	Quarter
🇺🇸 Dallas Fed Manufacturing Delivery Index	2.8 points	-3 points	Monthly
🇺🇸 Dallas Fed Manufacturing Employment Index	-2.9 points	-5.3 points	Monthly
🇺🇸 Dallas Fed Manufacturing Index	-15.1 points	-19.4 points	Monthly
🇺🇸 Dallas Fed Manufacturing Prices Paid Index	21.5 points	20.4 points	Monthly
🇺🇸 Dallas Fed Manufacturing Production Index	0.7 points	-2.8 points	Monthly
🇺🇸 Dallas Fed New Order Index	-1.3 points	-2.2 points	Monthly
🇺🇸 Dallas Fed Service Sector Revenue Index	7.7 points	1.9 points	Monthly
🇺🇸 Dallas Fed Services Index	-4.1 points	-12.1 points	Monthly
🇺🇸 Durable Goods Orders	-0.8 %	-0.8 %	Monthly
🇺🇸 Durable Goods Orders Excluding Defense	-0.2 %	-0.5 %	Monthly
🇺🇸 Durable Goods Orders Excluding Transportation	0.5 %	-0.1 %	Monthly
🇺🇸 Factory Orders	-0.5 %	-0.8 %	Monthly
🇺🇸 Factory Orders Excluding Transportation	0.7 %	0.4 %	Monthly
🇺🇸 Grain Reserves Wheat	702 M Bushels	1.087 B Bushels	Quarter
🇺🇸 Industrial production	0.4 %	-0.7 %	Monthly
🇺🇸 Industrial Production MoM	0.9 %	0 %	Monthly
🇺🇸 ISM Manufacturing Backlog	44.1 points	43.6 points	Monthly
🇺🇸 ISM Manufacturing Deliveries	52.6 points	49.8 points	Monthly
🇺🇸 ISM Manufacturing Employment	49.3 points	51.1 points	Monthly
🇺🇸 ISM Manufacturing Inventory Levels	43.9 points	50.3 points	Monthly
🇺🇸 ISM Manufacturing Prices	52.1 points	57 points	Monthly
🇺🇸 ISM Manufacturing Production	45.9 points	48.5 points	Monthly
🇺🇸 ISM New Orders Manufacturing	49.3 points	45.4 points	Monthly
🇺🇸 ISM New Orders Non-Manufacturing	54.1 points	52.2 points	Monthly
🇺🇸 ISM Non-Manufacturing Business Activity	57.2 points	59.9 points	Monthly
🇺🇸 ISM Non-Manufacturing Employment	47.1 points	45.9 points	Monthly
🇺🇸 ISM Non-Manufacturing Prices	58.1 points	59.2 points	Monthly
🇺🇸 Kansas Fed Composite Index	-8 points	-2 points	Monthly
🇺🇸 Kansas Fed Employment Index	-2 points	-11 points	Monthly
🇺🇸 Kansas Fed Manufacturing Index	-11 points	-1 points	Monthly
🇺🇸 Kansas Fed Manufacturing Index	-13 points	-6 points	Monthly
🇺🇸 Kansas Fed Manufacturing Index	7 points	-12 points	Monthly
🇺🇸 Kansas Fed Paid Prices Index	19 points	18 points	Monthly
🇺🇸 Leading Indicator	101.2 points	101.7 points	Monthly
🇺🇸 LMI Logistics Manager Index Future	66.1 points	65.5 points	Monthly
🇺🇸 LMI Storage Costs	63.6 points	65.2 points	Monthly
🇺🇸 LMI Transport Prices	61 points	57.8 points	Monthly
🇺🇸 LMI Warehouse Prices	64.5 points	64.9 points	Monthly
🇺🇸 LMI-Logistics Manager Index	56.5 points	55.3 points	Monthly
🇺🇸 Manufacturing PMI	51.6 points	51.3 points	Monthly
🇺🇸 Manufacturing Production	-0.5 %	0 %	Monthly
🇺🇸 Manufacturing Production MoM	0.9 %	-0.4 %	Monthly
🇺🇸 Mining Production	-2.2 %	-0.9 %	Monthly
🇺🇸 New Orders	584.245 B USD	587.023 B USD	Monthly
🇺🇸 NFIB Business Optimism Index	90.5 points	89.7 points	Monthly
🇺🇸 NY Empire State Employment Index	-8.7 points	-6.4 points	Monthly
🇺🇸 NY Empire State Manufacturing Index	-6 points	-15.6 points	Monthly
🇺🇸 NY Empire State Manufacturing Index	-1 points	-16.5 points	Monthly
🇺🇸 NY Empire State Manufacturing Index	3.3 points	-1.2 points	Monthly
🇺🇸 NY Empire State Prices Paid Index	29 points	23.2 points	Monthly
🇺🇸 Orders for Capital Goods Excluding Defense and Aircraft	1 %	-0.9 %	Monthly
🇺🇸 Philadelphia Fed Manufacturing Index	1.3 points	4.5 points	Monthly
🇺🇸 Philly Fed Business Climate	36.7 points	15.8 points	Monthly
🇺🇸 Philly Fed CAPEX Index	12.1 points	20.1 points	Monthly
🇺🇸 Philly Fed Employment	-2.5 points	-7.9 points	Monthly
🇺🇸 Philly Fed New Orders	-2.2 points	-7.9 points	Monthly
🇺🇸 Philly Fed Prices Paid	22.5 points	18.7 points	Monthly
🇺🇸 PMI Non-Manufacturing Sector	53.8 points	49.4 points	Monthly
🇺🇸 Richmond Fed Manufacturing Index	-10 points	0 points	Monthly
🇺🇸 Richmond Fed Manufacturing Shipments	-9 points	13 points	Monthly
🇺🇸 Richmond Fed Services Index	3 points	-1 points	Monthly
🇺🇸 Services PMI	55.1 points	54.8 points	Monthly
🇺🇸 Soybean Grain Reserves	969 M Bushels	1.845 B Bushels	Quarter
🇺🇸 Steel production	6.7 M Tonnes	7 M Tonnes	Monthly
🇺🇸 Total Vehicle Sales	16 M	15.8 M	Monthly
🇺🇸 Vehicle Registrations	279,800	261,300	Monthly
🇺🇸 Wholesale Inventory Levels	0.6 %	0.2 %	Monthly

What is Retail Inventories Ex Autos?

Retail Inventories Ex Autos: An In-Depth Analysis In the intricate world of macroeconomic data, understanding the various categories can significantly aid in deciphering economic trends and making informed decisions. Among these categories, "Retail Inventories Ex Autos" holds a crucial position. This metric pertains to the value of retail inventories excluding the automotive sector. For professionals and analysts venturing into macroeconomic analysis, this parameter offers invaluable insights into the overall health of the retail industry and the economy at large. This detailed description explores the significance, implications, and dynamics of Retail Inventories Ex Autos, providing readers with a comprehensive understanding of its role within the broader macroeconomic framework. To begin with, retail inventories represent the total value of goods held in stock by retailers. These goods range from household items and apparel to electronics and groceries. However, the "Retail Inventories Ex Autos" category specifically excludes inventories related to the automotive sector, comprising vehicles, parts, and related items. By isolating the automotive industry, this metric offers a clearer picture of inventory levels and trends within the broader retail sector. The exclusion of automotive inventories from this metric is intentional and important. The automotive sector is often subject to unique market dynamics that can obscure broader retail trends. For instance, automobile inventories are heavily influenced by factors such as manufacturing cycles, dealership agreements, and vehicle sales trends which can be highly volatile. By focusing solely on non-automotive retail inventories, analysts can gain a more stable and representative overview of inventory trends across other retail categories. This allows for a more nuanced understanding of consumer behavior and retail strategies. One of the key reasons for closely monitoring Retail Inventories Ex Autos is its direct correlation with consumer demand and retail sales. When retailers observe strong consumer demand, they are likely to increase their inventory levels to meet anticipated future sales. Conversely, rising inventories can indicate slowing demand, leading to concerns about overstocking and potential markdowns. Therefore, fluctuations in this metric can serve as a leading indicator of economic health and consumer confidence. Moreover, Retail Inventories Ex Autos offers insights into supply chain efficiency and retail management. Retailers strive to balance the need for adequate inventory to meet customer demand with the cost implications of holding excess stock. Efficient inventory management ensures that retailers can respond quickly to changes in demand without incurring unnecessary costs. Therefore, shifts in inventory levels can highlight challenges in the supply chain, including disruptions, delays, or inefficiencies. Furthermore, this metric plays a crucial role in GDP (Gross Domestic Product) calculations. Retail inventories form a part of the broader inventory investment data that contributes to the GDP calculation. Changes in inventory levels, including Retail Inventories Ex Autos, can impact the determination of GDP growth or contraction. A significant increase in inventories might suggest that goods are not selling as expected, potentially leading to a future reduction in production and overall economic slowdown. Conversely, decreasing inventories might indicate strong sales and potential future production increases to replenish stock. Retail Inventories Ex Autos also have implications for inflation monitoring and forecasting. Inventory levels can influence pricing strategies used by retailers. For example, high inventory levels may prompt retailers to reduce prices to clear excess stock, thereby contributing to lower inflation. Conversely, low inventory levels amidst strong demand can lead to price increases, contributing to inflationary pressures. Therefore, analyzing this metric can aid in predicting inflation trends and assisting policymakers in making informed decisions regarding monetary policy. Additionally, sectoral analysis benefits substantially from the Retail Inventories Ex Autos metric. Retail sectors such as clothing, electronics, household goods, and groceries each exhibit unique inventory characteristics and trends. By examining inventory data at a disaggregated level, analysts can gain insights into the performance and challenges facing specific retail sectors. This detailed understanding enables more targeted and effective decision-making for both businesses and policymakers. While Retail Inventories Ex Autos offer a wealth of insights, it is essential to interpret the data in conjunction with other economic indicators. Data on consumer spending, retail sales, and manufacturing output should be analyzed in tandem with inventory levels to draw comprehensive conclusions. Furthermore, external factors such as seasonal variations, economic policies, and global economic conditions can also influence inventory trends and should be considered in the analysis. At Eulerpool, we prioritize providing accurate and up-to-date macroeconomic data to help professionals make well-informed decisions. Our platform offers detailed and easily accessible data on Retail Inventories Ex Autos, alongside other crucial economic indicators. By leveraging our robust data resources, analysts, investors, and decision-makers can gain a deeper understanding of market dynamics and tailor their strategies accordingly. In conclusion, Retail Inventories Ex Autos is a critical metric in the realm of macroeconomic analysis. It provides essential insights into consumer demand, supply chain efficiency, inflation trends, and overall economic health. By excluding the automotive sector, this metric offers a more stable and representative view of the retail landscape. Thorough analysis of this parameter, in combination with other economic indicators, can significantly enhance the understanding of economic trends and inform effective decision-making strategies. At Eulerpool, our commitment to providing comprehensive and reliable data ensures that you have the tools necessary to navigate the complexities of macroeconomic analysis effectively.

Country

United States

Continent

America

Highest Value

3.8

Lowest Value

-2.1

Average Value

0.29

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