Industrialization, which is currently taking place in the world under new technological conditions, guarantees successful economic development. In this regard, analysts, entrepreneurs, government officials, politicians at the local and national levels are interested in timely and reliable information about the state and prospects for the development of the national industry. To get signals about changes in economic activity in the near future, economists use leading indicators – dynamic data series that demonstrate a fairly stable connection with the basic data series of the macroeconomic development cycle in a particular country. However, in connection with the peculiarities of development, each state has to find its own solutions in this subject area. The article focuses on leading indicators of industry development. The objectives of the work are to generalize the accumulated experience in the field of short-term forecasting of industry based on the use of the dynamics of indicators that have a leading connection with industrial production, and to substantiate recommendations regarding the possibilities of their use for short-term forecasting of the industrial development of Ukraine.

As a result of the generalization of the world experience of using leading indicators, considering the national industrial specifics, two working hypotheses were suggested in the research process.

The first one is based on the fact that (a) when forecasting the turning points of economic activity in the national industry, it is necessary to focus on general and specific leading indicators of countries that are the main partners of Ukraine, especially those to which goods of the industrial group are exported; (b) the list of candidate indicators should include world energy prices, taking into account the significant dependence of national production on hydrocarbon imports; (c) in addition to the real money supply, the dynamics of industrial value added are influenced by other monetary factors, namely – the hryvnia exchange rate to the dollar and the index of the US dollar, which is explained by the openness of the national economy, its small size, specialization in the export of raw materials and significant dependence on the import of industrial goods, necessary to create products with high value added. For further verification of this hypothesis, it is offered to divide the relevant indicators into four groups: those based on the results of enterprise surveys, indicators of financial activity of enterprises, monetary and socio-economic indicators. At the same time, the availability of data and promptness of updating (at least quarterly) is a key condition for their inclusion in the selection of candidates.

The second working hypothesis is that the proposed indicators can serve as ones to provide early signals about the dynamics of the value added created in the industry. In order to verify it in practice, it is necessary to create a database of indicators that can be used to predict the dynamics of gross value added in industry, perform mathematical calculations (build quantitative dependencies of value added on selected indicators considering the time lag), integrate individual indicators into a composite index of industrial development. The subject of further research is solving these problems.

Adam, T., & Benecká, S. (2020). High-frequency indicators of economic activity during the Covid-19 pandemic. Czech National Bank. Retrieved from https://www.cnb.cz/en/monetary-policy/inflation-reports/boxes-and-annexes-contained-in-inflation-reports/High-frequency-indicators-of-economic-activity-during-the-Covid-19-pandemic/

Berk, J. M., & Bikker, J. A. (1995). International Interdependence of Business Cycles in the Manufacturing Industry: The Use of Leading Indicators for Forecasting and Analysis. Journal of Forecasting, 14, pp. 1-23.

Bums, A. F., & Mitchell, W. C., (1938) ‘Statistical indicators of cyclical revivals’, Bulletin 69, NBER, Cambridge, MA.

Burns, F., & Wesley, C. (1946). The Basic Measures of Cyclical Behavior. National Bureau of Economic Research.

Granger, C. W. J. (1980). Forecasting in Business and Economics, New York Academic Press.

Hecht, A. & Boyle, M. J. (2022). Higher Interest Rates and Commodity Prices. Retrieved 9 March 2022. Retrieved from https://www.thebalance.com/commodity-prices-when-interest-rates-rise-4084273

Moore, G. H. (1961). Business Cycle Indicators, Contributions to the Analysis of Current Business Conditions, NBER, Princeton University Press.

Nilsson, R. (2006). Composite Leading Indicators and Growth Cycles in Major OECD NonMember Economies and recently new OECD Members Countries. OECD Statistics Working Papers.

Nilsson, R. (2006). Composite Leading Indicators and Growth Cycles in Major OECD NonMember Economies and recently new OECD Members Countries. OECD Statistics Working Papers.

OECD (2022). OECD Composite Leading Indicators: Turning Points of Reference Series and Component Series. Retrieved from https://www.oecd.org/sdd/leading-indicators/CLI-components-and-turning-points.pdf

Persons, W. M. Forecasting Business Cycles. By. New York: John Wiley & Sons. Inc. 1931, pp. xiv+295.

Stadler, G.W. (1994). Real Business Cycles. Journal of Economic Literature, 32(4), pp. 1750-1783.

The Conference Board (2022). LEI for Germany Decreased in April. Retrieved from https://www.conference-board.org/topics/business-cycle-indicators/press/germany-global-lei-april-2022.

The Conference Board (2022). US Leading Indicators. Retrieved from https://www.conference-board.org/topics/us-leading-indicators.

Trading Economics (2022). Turkey Leading Economic Index. Retrieved from https://tradingeconomics.com/turkey/leading-economic-index.

UN. Economic and Social Council (2014). An in-depth analysis of leading, composite and psychological indicators. Paris.

Weidenhammer, R. (1932). [Review of Forecasting Business Cycles., by W. M. Persons]. The Journal of Business of the University of Chicago, 5(1), pp. 98-101. Retrieved from http://www.jstor.org/stable/2349329

World Bank (2021). Causes and consequences of metal price shocks. Special Focus. Retrieved from https://www.worldbank.org/commodities

State Statistics Service of Ukraine (2020). Foreign trade of Ukraine. Kyiv.

State Statistics Service of Ukraine (2021). Ukraine's foreign trade in goods in 2021 (Express issue).

State Statistics Service of Ukraine (2022). Commodity structure of Ukraine's foreign trade in 2021.

Kondratev, N. D., Yakovets, Yu. V., & Abalkin, L. I. (2002) Big business cycles and the theory of prediction. Selected works. Moskow: Ekonomika.

Smirnov, S. (2001). Leading indicator system for Russia. Voprosy Ekonomiki, 3, pp. 23-42.

Tabolov, A. (2007). System of leading indicators for the Republic of Belarus. Bankaŭski veśnik, 11, pp. 30-36.

Federation of Robotic Workers of Ukraine (2021). Through the price of gas, 91% of industrial enterprises, fed by the FRU, will become overwhelmed. Retrieved from https://fru.ua/ua/media-center/news/fru/cherez-tsinu-na-gaz-u-zhovtni-stanut-zbitkovimi-91-promislovikh-pidpriemstv-opitanikh-fru-u-perspektivi-skorochennya-robochikh-mists-ta-nadkhodzhen-do-byudzhetiv

Hansen, E. (1959). Business cycles and national income. Moskow: Inostrannaya literatura. 760 p.