Graph and download economic data for Industrial Production: Manufacturing (NAICS) (IPMAN) from Jan 1972 to May 2025 about NAICS, headline figure, IP, production, manufacturing, industry, indexes, and USA.

Industrial Production in Japan decreased 2.40 percent in May of 2025 over the same month in the previous year. This dataset provides - Japan Industrial Production - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Although it was not a united country until 1871, industrialization across Germany began in the early 1800s, and it quickly saw Germany emerge as a Great Power in Europe. German industrialization was largely driven by coal and steel production, of which Germany had rich deposits, and these were used in construction and infrastructure to modernize the country. The mechanization of agriculture also fed into this, as many people from rural regions flocked to cities in search of work. Many of the coal and iron deposits were located in Germany's west, particularly around the Rhine and Ruhr regions, and industry here benefitted from strong rail and water transport networks. Today, with over five million inhabitants, the Ruhr region is the most populous metropolitan area in the country, largely due to these developments. While Germany was among the most advanced nations in the world by the end of the 19th century, industrial output grew higher still in the 20th; between 1896 and 1913, industrial output in Germany doubled. Interwar turmoil After the First World War, Germany lost its resource rich territories of Alsace-Lorraine and the Saarland, while the Rhine and Ruhr regions were also occupied by France, and much of its industrial output was sent to other countries as war reparations. Hyperinflation in 1923 also saw the collapse of the German economy, and it was not until the late-1920s that economic recovery from the war truly began, although this was also short-lived. As Germany had been dependent on financial aid from the U.S. in order to recover and meet its reparation payments, the Great Depression in the U.S. had dire consequences for the German economy. From 1929 until 1932, industrial output fell once more, and many historians point to this economic difficulty as a catalyst for the rise of nationalism and fascism in Germany. The Nazi Party then ascended to power in 1933, the year the Depression ended, and the economy was restructured to support a war of expansion. Among other factors, this involved tax breaks for large businesses, allowing cartels to control local business, increasing average working hours, and prioritizing industrial employment by importing food from the east. The strength of Germany's industry then allowed the Axis powers to take control of most of Europe during the Second World War, but it was ultimately defeated by 1945. Post-war split Following the war, Germany was split into two separate states; commonly referred to as East and West Germany. The west was a liberal democracy with a free-market economy, while the east was a communist state with a command economy, yet both became leaders in their respective trading blocks during the Cold War. When looking at industrial growth over the next three decades, using output in 1963 as a benchmark, East Germany's output grew over nine times larger from 1949 to 1975, whereas West Germany's grew by a factor of six. It is important to remember, however, that the west was larger, more populous, and starting from a more industrially developed point than the east, therefore it was consistently more advanced. The West also had fewer restrictions placed on it from other nations after the war, and it played a leading role in European integration; whereas the East was influenced more heavily by the USSR and it had less trade with other advanced nations, which hindered its technological development. West Germany's output took a hit in the 1970s due to the 1973-1975 Recession, whereas the East's economy was protected as it had little trade with the U.S. and its partners. However, the West quickly recovered and economic stagnation in the East throughout the 1980s would contribute to the eventual collapse of the Eastern Bloc, and Germany was officially reunified in 1990.

EU motor vehicle production output nosedived amid the outbreak of the coronavirus crisis. In April 2020, the motor vehicle manufacturing industry across the 27 European member states had a volume index of only 19.4 compared with the 2021 baseline of 100. While production volume started to rebound in May 2020, the global automotive semiconductor shortage had led to a slow slump of the volume index through March 2022, and production had been fluctuating again in 2023 and 2024, with Germany's particularly declining. Production slows down amid pandemic lockdown France, Spain, and Germany are among the leading producers of motor vehicles worldwide. The production index decreased in all of these countries and has not fully recovered from the outbreak of the coronavirus pandemic in Europe in the spring of 2020. The German motor vehicle production index, for instance, has been on the decline since September 2023, due to changes in the automotive industry in the country. The potential of tariffs from the United States in 2025 further suggests 2025 could be a complex year for the European Union's vehicle outout. The European motor vehicle manufacturing industry had around 2.4 million direct employees on the payroll, many of whom were faced with job insecurity from the onset of the pandemic. The COVID-19 pandemic forced factories to stop production in April 2020. Manufacturing facilities in most vehicle-producing regions have been affected after Europe became the outbreak's epicenter in mid-March. By July, many factories reopened, albeit at reduced capacities. European manufacturing firms rely on state aid to pay furloughed workers and prevent long-term plant closures. Supply chain uncertainties affect restart Production levels began to climb back towards the end of 2020. However, chip shortages and other supply chain uncertainties became the leading cause of concern between December 2020 and February 2022. As a result, Germany's motor vehicle production index dipped to 56.2 in March 2022, with other regional markets following the same pattern. France and Germany, consistently below the European average volume index from December 2023 to February 2025, were the markets with the highest turnover from motor vehicle and trailer manufacturing in the European Union in 2023.

In April 2025, the value of the Manufacturing Purchasing Leaders' Index (PLI) in the United States stood at ****. An indicator of the economic health of the manufacturing sector, the Purchasing Leaders' Index is based on five major indicators: new orders, inventory levels, production, supplier deliveries and the employment environment. An index value above ** percent indicates a positive development in the manufacturing sector, whereas a value below ** percent indicates a negative situation.

The Forklift Manufacturing industry primarily manufactures forklifts, also known as industrial trucks, which are small- to midsize material-handling vehicles used to lift and carry heavy loads from one location to another. Forklifts are mainly used by construction, manufacturing and freight-handling industries. Growth in these industries underpins demand for forklifts produced by manufacturers. Revenue growth has been stunted overall because of suspended trade and industrial production activity amid the COVID-19 pandemic. Many companies suspended their operations temporarily because of government restrictions. Still, restrictions have substantially eased, enabling activity within the industrial production sector to resume. Still, industry revenue has been shrinking at a CAGR of 0.6% through the end of 2024 to reach $12.9 billion, including an expected dip of 0.7% in 2024 alone. Overall, increasing demand has pushed up the total number of skilled employees. Because of the volatile nature of steel prices, fluctuating purchase costs significantly impact profit. Average industry profit, measured as earnings before interest and taxes, is expected to account for 4.5% of revenue in 2024, down from 5.8% in 2019. An expansion in demand will likely drive up industry participation levels and lead to higher profit in the coming years. Most notably, the most prominent companies, like Crown Equipment Corporation and Hyster-Yale Materials Handling Inc., are expected to expand domestic operations. Revenue is expected to gain as the industrial production index continues its upward momentum and the value of nonresidential construction bounces back. Also, projects funded by the Infrastructure Investment & Jobs Act (IIJA) will fuel steady demand from the construction sector. With increases in demand from downstream markets, industry revenue is expected to hike at a CAGR of 1.1% to $13.7 billion through the end of 2029, with profit anticipated to also remain relatively steady. Exports as a revenue share are also expected to swell as the US Dollar depreciates and US manufacturers capitalize on trade gaps created by international tensions. The expansion will accommodate rising demand, with industrial enterprises and establishments increasing in the coming years.

This table presents information about developments in production and turnover in industry (excl. construction), SIC 2008 sections B - E. The data can be divided by a number of branches according to Statistics Netherlands' Standard Industrial Classification of all Economic Activities 2008 (SIC 2008). Developments are presented as percentage changes compared to a previous period and by means of indices. In this table, the base year is updated to 2015, in previous publications the base year was 2010.

Developments in turnover and volume are published in two formats. Firstly, in the form of year-on-year changes relative to the same period in the preceding year. These figures are shown both unadjusted and adjusted for calendar effects. The second format pertains to period-on-period changes, for example quarter-on-quarter. Period-on-period changes are calculated by applying seasonal adjustment.

Data available from: January 2005

Changes as of 10 July 2019: The figures of May 2019 have been added to the table. The figures of April 2019 have been adjusted.

Changes as of 7 June 2019: The figures of April 2019 have been added to the table. The figures of January through March 2019 have been adjusted. The working day- and seasonal-adjustmentmodels have been updated, leading to the data back to january 2018 being revised and set to definitive.

Changes as of 10 May 2019: The figures of March 2019 have been added to the table. The figures of January and February 2019 have been adjusted.

Changes as of 9 April 2019: The figures of February 2019 have been added to the table. The figures of 2018 and January 2019 have been adjusted, and all of the 2017 data has been finalized. Domestic and foreign turnover of Mining and quarrying, which were previously undisclosed, have now been published.

The underlying coding of the following classifications used in this table has been adjusted: - Manufacture of capital goods - Manufacture of consumer goods - Manufacture of durable consumer goods - Manufacture of intermediate goods - Manufacture of non-durable consumergoods

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 10 December 2018: The production figures till October 2018 have been added to the table. The turnover figures of October 2018 have also been added.

Changes as of 9 November 2018: Turnover figures of industry for the month September 2018 have been added.

Changes as of 8 June 2018: Turnover figures of industry for the month April 2018 have been added. For the calculation of the average day and seasonal adjusted turnover new setups have been implemented from January 2017 onwards.

Changes as of 9 April 2018: Turnover figures of industry for the month February 2018 have been added. Turnover figures for January 2017 up to and including January 2018 have also been revised, because updated information was processed.

When will new figures be published? As a rule, monthly statistics are published six to eight weeks after the end of the reporting month. Quarterly statistics are published on the last working day of the second month after the quarter. After completing the base year change production figures will be included in this table. For production figures see link in section 3.

Status of the figures: The figures of a calendar year will become definite no later than five months after the end of that calendar year. Until then, the figures in this table will be “provisional” and can still be adjusted as a result of delayed response. Currently, the monthly turnover figures of 2018 are definitive. Once definitive figures have been published, Statistics Netherlands will only revise the results if significant adjustments and/or corrections are necessary.

Graph and download economic data for Producer Price Index by Industry: Total Manufacturing Industries (PCUOMFGOMFG) from Dec 1984 to Jun 2025 about manufacturing, PPI, industry, inflation, price index, indexes, price, and USA.

Graph and download economic data for Industrial Production: Manufacturing: Durable Goods: Raw Steel (NAICS = 3311,2pt.) (IPN3311A2RS) from Jan 1972 to Apr 2025 about steel, IP, durable goods, production, goods, industry, indexes, and USA.

Industrial product price index (IPPI), by major product group by North American Product Classification System (NAPCS) 2017 Version 2.0. Monthly data are available from January 1956. The table presents data for the most recent reference period and the last four periods. The base period for the index is (202001=100).

This table presents figures on turnover and production changes in Trade and Services sector. The figures can be broken down by industry according to Statistics Netherlands' Standard Industrial Classification of all Economic Activities 2008 (SIC 2008). The change is shown both as a percentage change compared to a previous period and through index figures with 2021 as base year. Turnover and production changes are published in two forms. Firstly, as year-on-year changes where the growth is expressed relative to the same period in the previous year. These figures are presented unadjusted and calendar-adjusted. The second form represents period-on-period changes: month-on-month and quarter-on-quarter. Period-on-period changes are possible by applying seasonal adjustment. Currently, this table exclusively comprises seasonally- and calendar adjusted data pertaining to monthly records for the retail sector. For other sectors, the unadjusted monthly series only extend back to January 2021, complicating the process of conducting adjustments. The lack of sufficient historical data makes it challenging to identify consistent patterns and trends, which is crucial for accurate adjustments. Some data may not be representative of all seasonal influences occurring over a longer period, potentially leading to less reliable or even incorrect adjustments. As the unadjusted monthly series lengthens, more reliable adjustments can be made. Therefore, in the spring of 2025, the table will be expanded to include seasonally- and calendar adjusted records for other sectors, retroactively from January 2021. Data available from: January 2000 for branches within SIC division 47 and first quarter of 2005 for all other branches. Status of figures: Figures for 2024 and 2025 are provisional. The figures of a calendar year become final no later than six months after the end of that calendar year. Due to delayed response, provisional figures may still change. Changes as of May 1, 2025: Figures of industries belonging to NACE sections G, H, I, J, L, M, N and S have been added. These are figures for the period March and the first quarter of 2025 as far as retail trade is concerned and February for other industries. Figures labeled as "provisional" may have been revised. To keep the results of these index series in line with current events, a so-called base year change is carried out once every five years. In 2024, the publication of this table switched from reference year 2015 to 2021 (2021=100) and the weighting factors were updated and based on the year 2021. This table combines data from 9 separate former tables. Which tables this concerns can be found later in this table explanation under "3. Links to relevant tables and articles". When are new figures released? For monthly business statistics, figures are published as a rule 2 months after the end of the reporting month, figures for the retail trade sector and imports of new passenger cars and light commercial vehicles are published 1 month after the end of the reporting month. After publication of final results, Statistics Netherlands adjusts the figures only if major adjustments and/or corrections are necessary.

Descriptive statistical results of variables at the world level.

Business Confidence in the United States increased to 49 points in June from 48.50 points in May of 2025. This dataset provides the latest reported value for - United States ISM Purchasing Managers Index (PMI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset package is focused on U.S construction materials and three construction companies: Cemex, Martin Marietta & Vulcan.

In this package, SpaceKnow tracks manufacturing and processing facilities for construction material products all over the US. By tracking these facilities, we are able to give you near-real-time data on spending on these materials, which helps to predict residential and commercial real estate construction and spending in the US.

The dataset includes 40 indices focused on asphalt, cement, concrete, and building materials in general. You can look forward to receiving country-level and regional data (activity in the North, East, West, and South of the country) and the aforementioned company data.

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Data is updated daily, has an average lag of 4-6 days, and history back to 2017.

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SpaceKnow offers 3 delivery options: CSV, API, and Insights Dashboard

Available Indices Companies: Cemex (CX): Construction Materials (covers all manufacturing facilities of the company in the US), Concrete, Cement (refinery and storage) indices, and aggregates Martin Marietta (MLM): Construction Materials (covers all manufacturing facilities of the company in the US), Concrete, Cement (refinery and storage) indices, and aggregates Vulcan (VMC): Construction Materials (covers all manufacturing facilities of the company in the US), Concrete, Cement (refinery and storage) indices, and aggregates

USA Indices:

Aggregates USA Asphalt USA Cement USA Cement Refinery USA Cement Storage USA Concrete USA Construction Materials USA Construction Mining USA Construction Parking Lots USA Construction Materials Transfer Hub US Cement - Midwest, Northeast, South, West Cement Refinery - Midwest, Northeast, South, West Cement Storage - Midwest, Northeast, South, West

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Index Methodology Summary Continuous Feed Index (CFI) is a daily aggregation of the area of metallic objects in square meters. There are two types of CFI indices; CFI-R index gives the data in levels. It shows how many square meters are covered by metallic objects (for example employee cars at a facility). CFI-S index gives the change in data. It shows how many square meters have changed within the locations between two consecutive satellite images.

How to interpret the data SpaceKnow indices can be compared with the related economic indicators or KPIs. If the economic indicator is in monthly terms, perform a 30-day rolling sum and pick the last day of the month to compare with the economic indicator. Each data point will reflect approximately the sum of the month. If the economic indicator is in quarterly terms, perform a 90-day rolling sum and pick the last day of the 90-day to compare with the economic indicator. Each data point will reflect approximately the sum of the quarter.

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Abstract

Introduction

The Annual Survey of Industries (ASI) is one of the large-scale sample survey conducted by Field Operation Division of National Sample Survey Office for more than three decades with the objective of collecting comprehensive information related to registered factories on annual basis. ASI is the primary source of data for facilitating systematic study of the structure of industries, analysis of various factors influencing industries in the country and creating a database for formulation of industrial policy.

The main objectives of the Annual Survey of Industries are briefly as follows:

(a) Estimation of the contribution of manufacturing industries as a whole and of each unit to national income.

(b) Systematic study of the structure of industry as a whole and of each type of industry and each unit.

(c) Casual analysis of the various factors influencing industry in the country: and

(d) Provision of comprehensive, factual and systematic basis for the formulation of policy.

The Annual Survey of Industries (ASI) is the principal source of industrial statistics in India. It provides statistical information to assess changes in the growth, composition and structure of organised manufacturing sector comprising activities related to manufacturing processes, repair services, gas and water supply and cold storage. The Survey is conducted annually under the statutory provisions of the Collection of Statistics Act 1953, and the Rules framed there-under in 1959, except in the State of Jammu & Kashmir where it is conducted under the State Collection of Statistics Act, 1961 and the rules framed there-under in 1964.

Geographic coverage

The ASI is the principal source of industrial statistics in India and extends to the entire country except Arunachal Pradesh, Mizoram & Sikkim and the Union Territory of Lakshadweep. It covers all factories registered under Sections 2m(i) and 2m(ii) of the Factories Act, 1948.

Analysis unit

The primary unit of enumeration in the survey is a factory in the case of manufacturing industries, a workshop in the case of repair services, an undertaking or a licensee in the case of electricity, gas & water supply undertakings and an establishment in the case of bidi & cigar industries. The owner of two or more establishments located in the same State and pertaining to the same industry group and belonging to census scheme is, however, permitted to furnish a single consolidated return. Such consolidated returns are common feature in the case of bidi and cigar establishments, electricity and certain public sector undertakings.

Universe

The survey cover factories registered under the Factory Act 1948.

Establishments under the control of the Defence Ministry,oil storage and distribution units, restaurants and cafes and technical training institutions not producing anything for sale or exchange were kept outside the coverage of the ASI.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Procedure

The sampling design followed in ASI 1998-99 is a Circular Systematic one. All the factories in the updated frame (universe) are divided into two sectors, viz., Census and Sample.

Census Sector: Census Sector is defined as follows:

a) All the complete enumeration States namely, Manipur, Meghalaya, Nagaland, Tripura and Andaman & Nicobar Islands. b) For the rest of the States/ UT's., (i) units having 200 or more workers, and (ii) all factories covered under Joint Returns.

Rest of the factories found in the frame constituted Sample sector on which sampling was done. Factories under Biri & Cigar sector were not considered uniformly under census sector. Factories under this sector were treated for inclusion in census sector as per definition above (i.e., more than 200 workers and/or joint returns). After identifying Census sector factories, rest of the factories were arranged in ascending order of States, NIC-98 (4 digit), number of workers and district and properly numbered. The Sampling was taken within each stratum (State X Sector X 4-digit NIC) with a minimum of 8 samples in each stratum in the form of 2 sub-samples. For the first time, all electricity undertakings other than captive units, Government Departmental undertakings such as Railway Workshops, P & T workshops etc. were kept out of coverage of ASI.

Sampling deviation

There was no deviation from sample design in ASI 1998-99.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Pre-data entry scrutiny was carried out on the schedules for inter and intra block consistency checks. Such editing was mostly manual, although some editing was automatic. But, for major inconsistencies, the schedules were referred back to NSSO (FOD) for clarifications/modifications.

The final unit level data of ASI 98-99 is available now in electronic media. This document describes additional information regarding ASI 98-99 data from the point of data processing. Users of ASI 98-99 data are requested to read this document carefully before they attempt to process the unit level data for their own purpose. They are also requested to refer to the schedule and the instruction manual for filling up the schedule before interpreting contents of various data fields. A. Contents The CD (or any other media) should contain the following files: ASI99.TXT This file contains unit level detail data of ASI 98-99 as per structure given in ANNEXURE- Total no. of records: 104740 XASI98.TXT (Metadata created from this .TXT file) This file contains unit level detail data of ASI 97-98 for those factories which were found not responding during the survey of ASI 98-99. The record layout is already available with the Computer Centre, New Delhi. Record Length: 135 Total no. of records: 6974 README.DOC This file.

B. Tabulation procedure The tabulation procedure by CSO(ISW) includes both the ASI 98-99 data and the extracted data from ASI 97-98 for all tabulation purpose. To make results comparable, users are requested to follow the same procedure. For calculation of various parameters, users are requested to refer instruction manual/report for the respective years. Please note that a separate inflation factor (Multiplier) is available for each factory against records belonging to Block-A ,pos:38-46 (Please refer ANNEXURE-I) for ASI 98-99 data. Since the data extracted from ASI 97-98 belong to Census Sector no such inflation (Multiplier) factor is required. Industry code as per Return(5-digit level of NIC-98) Industry code as reported by the factories in Block-A, Item 1 has been further codified because of the following two policies practiced at CSO(ISW). Tabulation policy: As per the latest tabulation policy, it has been decided to publish detail information regarding factories belonging to 01 to 37 of industry codes( 2-digit, NIC-98). Factories belonging to other industry groups would be clubbed together and to be published under 'Others'. Accordingly all industry codes other than 01 to 37 were replaced with a 5-digited code 'YYYYY'. Merging and suppression of identity: To suppress the identity of factories, less frequent industry codes were modified accordingly. Example: if a reported industry code is found as 2930Z, this is to be treated as 'other merged industry code under industry group 2930 (4-digit NIC'98)'. Similarly if the reported industry code is found as 293ZZ, the same as to be treated as 'other merged industry code under industry group 293 (3-digit NIC'98)' and so on.

FIXED ASSETS (Block-C) Columnwise relationship (please refer schedule) may not hold true for data in this block. This is because of the lack of information available from the factory owners. E. EMPLOYMENT AND LABOUR COST (Block-E) It has been found that a larger number of factory owners were unable to provide detailed break-up of information regarding provident fund (Block-E, Col.7). Instead they provide total provident fund as a whole for all employees (Block-E, Srl. No. 7, Col.7). Users are requested to use Srl.9, Col.7 for information on provident fund. The total of srl.6 to 8 for Col.7 may not tally with srl.9, col.7. F. ASICC codes in Block H, I & J Because of the proximity of various item's description, it is possible that same ASICC code may appear against multiple records in these blocks. They should not be treated as duplicates. They are clubbed together at the time of tabulation to provide information at ASICC level. G. Record Identification Key Record identification key for each factory is Despatch Serial No. (DSL, pos: 4-8) X Block code (Blk, pos: 3). Please refer ANNEXURE-I for item level identification key for each factory.

Sampling error estimates

Relative Standard Error (RSE) is calculated in terms of worker, wages to worker and GVA using the formula (Pl ease refer to Estimation Procedure document in external resources). Programs developed in Visual Faxpro are used to compute the RSE of estimates.

Data appraisal

To check for consistency and reliability of data the same are compared with the NIC-2digit level growth rate at all India Index of Production (IIP) and the growth rates obtained from the National Accounts Statistics at current and constant prices for the registered manufacturing sector.

Results of pvar2 estimation under different industry groups (some main results).

Graph and download economic data for Producer Price Index by Industry: Corrugated and Solid Fiber Box Manufacturing: Corrugated Shipping Containers for Paper and Allied Products (PCU32221132221102) from Mar 1980 to Jun 2025 about fiber, paper, manufacturing, PPI, industry, inflation, price index, indexes, price, and USA.

Abstract

The Annual Survey of Industries (ASI) is the principal source of industrial statistics in India. It provides statistical information to assess changes in the growth, composition and structure of organised manufacturing sector comprising activities related to manufacturing processes, repair services, gas and water supply and cold storage. Industrial sector occupies an important position in the State economy and has a pivotal role to play in the rapid and balanced economic development. The Survey is conducted annually under the statutory provisions of the Collection of Statistics Act 1953, and the Rules framed there-under in 1959, except in the State of Jammu & Kashmir where it is conducted under the State Collection of Statistics Act, 1961 and the rules framed there-under in 1964.

Geographic coverage

Coverage of the Annual Survey of Industries extends to the entire Factory Sector, comprising industrial units (called factories) registered under section 2(m)(i) and 2(m)(ii) of the Factories Act.1948, wherein a "Factory", which is the primary statistical unit of enumeration for the ASI is defined as:-"Any premises" including the precincts thereof:- (i) wherein ten or more workers are working or were working on any day of the preceding twelve months, and in any part of which a manufacturing process is being carried on with the aid of power or is ordinarily so carried on, or (ii) wherein twenty or more workers are working or were working on any day of the preceding twelve months, and in any part of which a manufacturing process is being carried on without the aid of power. In addition to section 2(m)(i) & 2(m)(ii) of the Factories Act, 1948, electricity units registered with the Central Electricity Authority and Bidi & Cigar units, registered under the Bidi & Cigar Workers (Conditions of Employment) Act,1966 are also covered in ASI.

Analysis unit

The primary unit of enumeration in the survey is a factory in the case of manufacturing industries, a workshop in the case of repair services, an undertaking or a licensee in the case of electricity, gas & water supply undertakings and an establishment in the case of bidi & cigar industries. The owner of two or more establishments located in the same State and pertaining to the same industry group and belonging to same scheme (census or sample) is, however, permitted to furnish a single consolidated return. Such consolidated returns are common feature in the case of bidi and cigar establishments, electricity and certain public sector undertakings.

Universe

The survey cover factories registered under the Factory Act 1948. Establishments under the control of the Defence Ministry,oil storage and distribution units, restaurants and cafes and technical training institutions not producing anything for sale or exchange were kept outside the coverage of the ASI.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design followed in ASI 1983-84 is a stratified unistage with StateXNIC 3 digit as stratum. All the factories in the updated frame (universe) are divided into two sectors, viz., Census and Sample.

a) CENSUS : The Census sector comprised of all big units with 50 or more workers and using power or 100 or more workers without using power and all electricity undertakings. All industrial units belonging to the 12 less industrially developed states/ UT's like Goa, Himachal Pradesh, J & K, Chandigarh, Manipur, Meghalaya, Nagaland, Tripura, Daman & diu, Pondicherry Dadra & Nagar Haveli, and Andaman & Nicobar Islands etc. were also enumerated every year along with the census units.

b) The rest of of the universe was covered on sampling design adopting State X 3 digit industry group as stratum so as to cover all the units in a span of two consecutive years (50% samples in alternate years).

*****Multiplier : How to apply the Multiplier :

      (i)  If Scheme Code = 1 then  Multiplier = 1
          If Scheme Code = 2 then  Multiplier = 2

(ii) During Processing/Tabulating apply the multiplier to each characteristics.

Sampling deviation

There was no deviation from sample design in ASI 1983-84.

Mode of data collection

Face-to-face [f2f]

Research instrument

Annual Survey of Industries Questionnaire (in External Resources) is divided into different blocks:

BLOCK1/2/16 : RECORD TYPE 011 : IDENTIFICATION PARTICULARS (Filled by CSO and Industrial Units) BLOCK 4 : RECORD TYPE 011 : SCHEDULE OF FIXED ASSETS BLOCK 4A : RECORD TYPE 011 : EMPLOYMENT AND LABOUR COST BLOCK 5 : RECORD TYPE 011 : SCHEDULE OF WORKING CAPITAL AND LOANS
BLOCK 6 : RECORD TYPE 011 : WORKING DAYS AND SHIFTS BLOCK 7 : RECORD TYPE 011 : EMPLOYMENT BLOCK 8 : RECORD TYPE 011 : LABOUR COST (INCLUDING FOR CONTRACT LABOUR) BLOCK 9 : RECORD TYPE 011 : FUELS, ELECTRICITY AND WATER CONSUMED (EXCLUDING INTERMEDIATE PRODUCTS) BLOCK 10 : RECORD TYPE 011 : OTHER EXPENDITURE BLOCK 11 : RECORD TYPE 011 : OTHER OUTPUT/RECEIPTS BLOCK 12 : RECORD TYPE 011 : ELECTRICITY BLOCK 13 : RECORD TYPE 011 : MATERIALS CONSUMED BLOCK 13 A : RECORD TYPE 011 : INPUT ITEMS (indigenous items consumed) BLOCK 13 B : RECORD TYPE 011 : INPUT ITEMS – directly imported items only (consumed) BLOCK 14 : RECORD TYPE 011 : PRODUCTS AND BY-PRODUCTS (manufactured by the unit) BLOCK 14 A : RECORD TYPE 011 : DISTRIBUTIVE EXPENSES

Cleaning operations

Pre-data entry scrutiny was carried out on the schedules for inter and intra block consistency checks. Such editing was mostly manual, although some editing was automatic. But, for major inconsistencies, the schedules were referred back to NSSO (FOD) for clarifications/modifications.

Code list, State code list, Tabulation program and ASICC code are also may be refered in the External Resources which are used for editing and data processing as well..

Sampling error estimates

Relative Standard Error (RSE) is calculated in terms of worker, wages to worker and GVA using the formula. Programs developed in Visual Foxpro are used to compute the RSE of estimates.

Data appraisal

To check for consistency and reliability of data the same are compared with the NIC-2digit level growth rate at all India Index of Production (IIP) and the growth rates obtained from the National Accounts Statistics at current and constant prices for the registered manufacturing sector.

Unit root test results of the time series data (2000–2018).

Graph and download economic data for Producer Price Index by Industry: Soap and Other Detergent Manufacturing: Commercial, Industrial, and Institutional Laundry Detergents (PCU32561132561112) from Jun 2007 to Jun 2025 about laundry, commercial, manufacturing, PPI, industry, inflation, price index, indexes, price, and USA.