Graph and download economic data for Producer Price Index by Commodity: Processed Foods and Feeds: Formula Feeds (WPS029301) from Jan 2005 to Aug 2025 about processed, food, commodities, PPI, inflation, price index, indexes, price, and USA.

United States PPI: Weights: PO: Formula Feeds data was reported at 0.413 % in 2024. This records a decrease from the previous number of 0.432 % for 2023. United States PPI: Weights: PO: Formula Feeds data is updated yearly, averaging 0.381 % from Dec 2007 (Median) to 2024, with 18 observations. The data reached an all-time high of 0.469 % in 2022 and a record low of 0.266 % in 2007. United States PPI: Weights: PO: Formula Feeds data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.I068: Producer Price Index: by Commodities: Weights.

United States PPI: Processed Foods: Animal Feeds: Formula Feeds data was reported at 203.500 1982=100 in Sep 2018. This records a decrease from the previous number of 206.800 1982=100 for Aug 2018. United States PPI: Processed Foods: Animal Feeds: Formula Feeds data is updated monthly, averaging 109.100 1982=100 from Jan 1962 (Median) to Sep 2018, with 681 observations. The data reached an all-time high of 272.900 1982=100 in Sep 2012 and a record low of 44.200 1982=100 in Feb 1962. United States PPI: Processed Foods: Animal Feeds: Formula Feeds data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.I017: Producer Price Index: By Commodities.

Graph and download economic data for Producer Price Index by Commodity: All Commodities (PPIACO) from Jan 1913 to Aug 2025 about commodities, PPI, inflation, price index, indexes, price, and USA.

United States - Producer Price Index by Commodity: Processed Foods and Feeds: Formula Feeds was 255.57500 Index 1982=100 in August of 2025, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Commodity: Processed Foods and Feeds: Formula Feeds reached a record high of 303.93800 in September of 2022 and a record low of 113.40000 in February of 2005. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Commodity: Processed Foods and Feeds: Formula Feeds - last updated from the United States Federal Reserve on October of 2025.

Japan PPI: W: FBTF: Feedstuff: Formula Feeds data was reported at 4.200 Per 1000 in Dec 2016. This stayed constant from the previous number of 4.200 Per 1000 for Nov 2016. Japan PPI: W: FBTF: Feedstuff: Formula Feeds data is updated monthly, averaging 4.200 Per 1000 from Jan 1980 (Median) to Dec 2016, with 444 observations. The data reached an all-time high of 4.200 Per 1000 in Dec 2016 and a record low of 4.200 Per 1000 in Dec 2016. Japan PPI: W: FBTF: Feedstuff: Formula Feeds data remains active status in CEIC and is reported by Bank of Japan. The data is categorized under Global Database’s Japan – Table JP.I097: Producer Price Index: 2010=100: Weight.

Japan PPI: BF: Feeds & Organic Fertilizers: Feeds: Formula Feeds data was reported at 155.800 2020=100 in Mar 2025. This records a decrease from the previous number of 157.400 2020=100 for Feb 2025. Japan PPI: BF: Feeds & Organic Fertilizers: Feeds: Formula Feeds data is updated monthly, averaging 70.900 2020=100 from Jan 1980 (Median) to Mar 2025, with 543 observations. The data reached an all-time high of 180.400 2020=100 in Oct 2022 and a record low of 48.700 2020=100 in Jun 1988. Japan PPI: BF: Feeds & Organic Fertilizers: Feeds: Formula Feeds data remains active status in CEIC and is reported by Bank of Japan. The data is categorized under Global Database’s Japan – Table JP.I043: Producer Price Index: 2020=100: Beverages & Foods.

This table contains figures on the average price development of the selling prices, the import prices and the domestic consumption of industrial products with a base year of 2015=100. This data is available for both domestic and foreign sales. The products are classified based on the goods classification PRODCOM (PRODuction COMmunautaire).

Data available from: January 2012

Status of the figures: The figures in this table are provisional during five months.

Changes as of March 30th 2018 For the first published period (2012), incorrect year on year developments were published. In this version of the table these figures are removed.

Changes as of July 4th 2018 The figures for product group B (Mining and quarrying) for the reporting period September to November 2017 were not correct due to an error in an underlying series. This has been corrected in this version. The figures for the product groups 20143000 (Industrial monocarboxylic fatty acids) and 20144000 (Organic compounds with nitrogen functions) for the reporting period September to November 2017 have been adjusted due to new information. Due to an incorrect calculation, a number of month-on-month developments and year-on-year developments were wrongly marked as unknown, insufficiently reliable or confidential. This has been corrected in this version.

Changes as of July 13th 2018 The underlying coding of classifications used in this table has been adjusted. It is now in line with the standard encoding defined by CBS. The structure and data of the table have not been adjusted.

Changes as of September 28th. Due to an incorrect calculation, a number of month-on-month developments and year-on-year developments were wrongly marked as unknown, insufficiently reliable or confidential for reporting period January 2018. This has been corrected in this version. Also new figures of the month August 2018 have been added.

When will new figures be published? New figures will be published not later than 30 days after the period under review.

Japan PPI: FBTF: Feedstuff: Formula Feeds data was reported at 114.000 2010=100 in Dec 2016. This records an increase from the previous number of 113.800 2010=100 for Nov 2016. Japan PPI: FBTF: Feedstuff: Formula Feeds data is updated monthly, averaging 78.100 2010=100 from Jan 1980 (Median) to Dec 2016, with 444 observations. The data reached an all-time high of 136.600 2010=100 in Jul 2014 and a record low of 56.400 2010=100 in Jun 1988. Japan PPI: FBTF: Feedstuff: Formula Feeds data remains active status in CEIC and is reported by Bank of Japan. The data is categorized under Global Database’s Japan – Table JP.I078: Producer Price Index: 2010=100: Food, Beverages, Tobacco & Feedstuffs.

Korea PPI: Commodities: Infant Formula Milk Powder data was reported at 118.600 2005=100 in Nov 2012. This stayed constant from the previous number of 118.600 2005=100 for Oct 2012. Korea PPI: Commodities: Infant Formula Milk Powder data is updated monthly, averaging 52.940 2005=100 from Jan 1965 (Median) to Nov 2012, with 575 observations. The data reached an all-time high of 118.600 2005=100 in Nov 2012 and a record low of 5.178 2005=100 in Jun 1965. Korea PPI: Commodities: Infant Formula Milk Powder data remains active status in CEIC and is reported by The Bank of Korea. The data is categorized under Global Database’s South Korea – Table KR.I037: Producer Price Index: Commodities: 2005=100.

Abstract

Transition to free economic structure and, as a consequence, processes of privatization of large agricultural and industrial organizations and birth of numerous new economic entities led to significant changes in quantitative and qualitative characteristics of industrial organizations and peasant farms in RA. During the last decade and especially the last 4-5 years, the structural changes, in their turn, caused also certain complications in the mentioned fields in terms of ensuring collection, comprehensiveness and reliability of statistical data on prices and pricing.

In particular, in case of radical structural changes, international recommendations require the weights upon which price indexes are based to be periodically updated. In order to have a real picture and dynamics of the present situation on creation of indicators for new base year, i.e. collection of information on set of goods-representatives, their weights, average annual prices, prices and price changes, it would be necessary to periodically conduct sample surveys for further improvement of the methodology for price index calculation.

The objectives of the survey were: • to improve the sample, develop a new sample, • to revise the base year and weights, • to receive additional information on prices of sales of industrial, agricultural product and purchase (acquisition of production means) in RA, • to improve methodology for price observation and calculation of price indexes (survey technology, price and other necessary data collection, processing, analyzing), • to revise the base year for producer price indexes, components structure, shares, calculation mechanism, etc., • to derive price indexes that would be in line with the international definitions, standards and classifications, • to complement the NSS RA price indexes database and create preconditions for its regular updating, • to update the information on economic units covered by price indexes calculation, • to ensure use of international standards and classifications in statistics, • to form preconditions for extension of sample observation mechanisms in the state statistics.

Besides the above mentioned, the need of the given survey was also stipulated by the following reasons: - a great mobility of micro-sized, small and medium-sized organizations mainly caused by increased speed of their births, activity and produced commodity changes or deaths that decreases the opportunity to create long-term fixed-base time series of prices and price indexes, - According to the CPA classification coding and recoding activities related to the introduction of Armenian classification of economic activities - NACE (based on the European Communities’ NACE classification).

Geographic coverage

National

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE DESIGN

Agriculture The sample of the survey was desighned in the conditions of lack of farm register. The number of peasant farms was calculated and derived by database analysis. The number of villages (quotas) selected from each marz was determined taking into account the percent of rural population of marzes. The villages from marz were selected randomly. The peasant farms covered by the survey were selected based on number of privatized plots. The survey was carried out in 200 rural communities selected from 10 marzes, in 5-20 households from each community. Pilot survey was conducted with 1 901 farms in the sample.

Industry The sample frame for the survey was designed as follows: 1. The industrial organizations with share 5 and more percent have been selected by reduction method from fifth level (each subsection) of NACE for whole RA industry. 476 out of 2231 industrial organizations covered by statistical observation were selected for pilot survey.

1. 70 organizations suggested by Industry statistics division of NSS RA and 70 organizations included in state observations on prices conducted previously by the NSS RA (in all 140 organizations), which are considered important and representative for price observation and excluded from the above-mentioned sample, were separated from the general population. These organizations have also been included in sample population of the pilot survey. As it became obvious from further work, the sample covered both the large and medium-sized and the small and micro-sized organizations, which ensured the representativeness of separate branches of industry and organizations by size. As a result, given by the objective of the survey, as well as available financial constraints, the sample population of the pilot survey comprised 616 industrial organizations, the volumes of produced production of whichaccording to the data for January-October of 2006 comprised more than 86% of total volume of RA industrial production. 165 (92.7%) out of 178 classes of NACE were covered by the sample.

Mode of data collection

Face-to-face [f2f]

Non-alcoholic fatty liver disease (NAFLD) has become the most prevalent liver disease in China. Sinisan (SNS) is a traditional Chinese medicine formula that has been widely used in treating chronic liver diseases, including NAFLD. However, its underlying biological mechanisms are still unclear. In this study, we employed a network pharmacology approach consisting of overlapped terms- (genes or pathway terms-) based analysis, protein-protein interaction (PPI) network-based analysis, and PPI clusters identification. Unlike the previous network pharmacology study, we used the shortest path length-based network proximity algorithm to evaluate the efficacy of SNS against NAFLD. And we also used random walk with restart (RWR) algorithm and Community Cluster (Glay) algorithm to identify important targets and clusters. The screening results showed that the mean shortest path length between genes of SNS and NAFLD was significantly smaller than degree-matched random ones. Six PPI clusters were identified and ten hub targets were obtained, including STAT3, CTNNB1, MAPK1, MAPK3, AGT, NQO1, TOP2A, FDFT1, ALDH4A1, and KCNH2. The experimental study indicated that SNS reduced hyperlipidemia, liver steatosis, and inflammation. Most importantly, JAK2/STAT3 signal was inhibited by SNS treatment and was recognized as the most important signal considering the network pharmacology part. This study provides a systems perspective to study the relationship between Chinese medicines and diseases and helps to discover potential mechanisms by which SNS ameliorates NAFLD.

There was the formula used in study to evaluate β-cell function.FPI: Fasting plasma insulin; FPG: Fasting plasma glucose; G: Mean plasma glucose;I: Mean plasma insulin; PPI: Postprandial plasma insulin; PPG: Postprandial plasma glucose; FPP: Fasting plasma proinsulin; PPP: Postprandial plasma proinsulin

Calculation of population prediction interval (PPI).

Variables required for the calculation of each prognostic score.

生产者价格指数（PPI）：BF：饲料和有机肥料：饲料：配制饲料在03-01-2025达155.8002020=100，相较于02-01-2025的157.4002020=100有所下降。生产者价格指数（PPI）：BF：饲料和有机肥料：饲料：配制饲料数据按月更新，01-01-1980至03-01-2025期间平均值为70.9002020=100，共543份观测结果。该数据的历史最高值出现于10-01-2022，达180.4002020=100，而历史最低值则出现于06-01-1988，为48.7002020=100。CEIC提供的生产者价格指数（PPI）：BF：饲料和有机肥料：饲料：配制饲料数据处于定期更新的状态，数据来源于日本銀行，数据归类于全球数据库的日本 – Table JP.I043: Producer Price Index: 2020=100: Beverages & Foods。

生产者价格指数（PPI）：FBTF：饲料：配制饲料在12-01-2016达114.0002010=100，相较于11-01-2016的113.8002010=100有所增长。生产者价格指数（PPI）：FBTF：饲料：配制饲料数据按月更新，01-01-1980至12-01-2016期间平均值为78.1002010=100，共444份观测结果。该数据的历史最高值出现于07-01-2014，达136.6002010=100，而历史最低值则出现于06-01-1988，为56.4002010=100。CEIC提供的生产者价格指数（PPI）：FBTF：饲料：配制饲料数据处于定期更新的状态，数据来源于日本銀行，数据归类于全球数据库的日本 – 表 JP.I078：生产者价格指数：2010年=100：食品、饮料、烟草和饲料。

生产者价格指数（PPI）：商品：MI：FT：PF：DP：婴儿配方奶粉在05-01-2008达107.9002000年=100，相较于04-01-2008的107.9002000年=100保持不变。生产者价格指数（PPI）：商品：MI：FT：PF：DP：婴儿配方奶粉数据按月更新，01-01-1965至05-01-2008期间平均值为53.1702000年=100，共521份观测结果。该数据的历史最高值出现于04-01-2007，达110.4002000年=100，而历史最低值则出现于06-01-1965，为5.3232000年=100。CEIC提供的生产者价格指数（PPI）：商品：MI：FT：PF：DP：婴儿配方奶粉数据处于定期更新的状态，数据来源于한국은행，数据归类于Global Database的韩国 – 表 KR.I038：生产者价格指数：商品：2000年=100。

Fit indices for proposed PPI-R factor structures analysed by Exploratory Structural Equation Modeling (ESEM).