CC BY
41
UDC 339.13:669.015
V. Gonchar,
DrHab (Economics), Priazovskyi state technical university, Mariupol, Ukraine
FORECASTING AS A METHOD OF METALS MARKETING RESEARCH
Setting the problem. The problem of predicting the dynamics of the steel market, demand and supply on the basis of general economic trends is defined. High export dependence metallurgical industry in Ukraine led to the need to examine current trends in the world market, and identify potential sources of competition in the future. The analysis of existing speaker characteristic steel markets in different regions of the world is held. For analysis of the world market is divided into 8 regions: Asia, EU, Europe, CIS, Middle East, Africa, North and South America. The productions dynamics trends are evaluated. The modified method of forecasting the market is applied, based on data from the International Monetary Fund, GDP in the world and in steel production according to data from the International Steel Association from 2002 to 2015. The research results identified a close correlation of GDP and steel production volume in the world, Asia, the Middle East and Europe. The regions leaders and outsiders are distinguished after metallurgical production consumption analysis in the world. The demand level of the advanced economy was defined by the consumption per capita in developed countries of European Union. Based on this research, the production forecast is built in the world and in the Middle East, Asia, and Europe.
Statement of the problem. In the context of increasing goods and services market dynamism there is an objective necessity in conducting market research by using existing methods of forecasting market trends.
Effective solution to this problem directly affects the performance of the companies. Enterprises operating in the local market to determine the dynamics of the local market and to project the development of world trends in the local market. To enterprises engaged in foreign trade, a more complex task, which requires evaluation of a large number of factors. The impact on the internal factors and worldwide operating in the sector was identified. The performance of each company depends on building an effective marketing policy, which in turn depends on the accuracy of predicting the dynamics of markets. High export orientation of Ukrainian metallurgical enterprises increased the need to analyze the dynamics of the global steel market is. The average share of exports from 2002-2015 was estimated at level of 74.3%. More accurate assessment of market trends will give the opportunity to our metallurgists quickly coordinate types and amounts of products to market trends, and stimulate to build economic relations, in the regions where the expected growth in demand for the products.
The last research analysis. Problems of the theoretical aspects of forecasting market trends are reflected in the works of G. Kassel, V. Pareto, L. Walras, D. Hicks, A. Marshall, V.M. Glushkov, A.N. Efimov,
D. Bell, T. Gordon, B. de Jouvenel, D. Gabor, F. Polak, M.V. Bikeeva, N.E Egorova, S.N. Iliashenko.
In spite of this big development of this topic in the economic theory, the effectiveness of forecasting methods by the market still needs further research. Forecasting techniques which have been effective in resent 1520 years show a dramatic reduction in its effectiveness due to the dynamism of economic factors. Forecasting dynamics in different sectors of the economy needs to be modified to suit individual methods of specific trends in the industry. Thus, in spite of a long study of the problem remains relevant and requires constant updating according to current market trends.
The purpose of the article is to provide marketing research of the steel market and forecast trends of regional steel markets, that are based on general development economic and economic systems indicators. It has been done a model of regional markets for the next 5 years, in order to predict the national producer's threat of competition from domestic producers of steel.
The main part.
Marketing is a complex and systematic process of collecting and analyzing information in order to reduce uncertainty and risk of decisions for business purposes. The main purpose of market research is to obtain information and ideas about the structure and dynamics trends of the market and enterprise opportunities to better adaptation its production structure, technology, product or service to the demand and the requirements of consumers [4].
Forecasting - is the scientific study of the prospects of humanity, the subject of which study is the future, and the product, the result of research by research findings on the state of the variant of the object [1].
A vital challenge confronting economists is how to forecast. The task is yet more exacting but ever more pertinent during a recession because livelihoods seem to depend on forecasts - will unemployment fall soon enough to stave off foreclosures?
Perhaps unsurprising then is a recent clash in the blogosphere over forecasting US GDP in the coming quarters. Greg Mankiw contested the US government's forecasts of GDP growth, questioning the trend station-arity assumption upon which the forecasts were made. Paul Krugman wrote an outraged response, accusing Mankiw of "evil wonkishness" [9]. Brad DeLong weighed in too, pointing out that a univariate analysis was "useless"; unemployment must be included in the analysis.
The exchange emphasises not just that economic variables are important in forecasts, but that econometric issues matter. If GDP is trend stationary, the implications are very different for forecasting than if GDP is
a random walk with drift - one will correct to some equilibrium, the other won't. Economic nuances matter too - what other variables make up this equilibrium relationship? Historically, there has been such a steady state, but whether that is the same one to which we will soon correct is unclear, and bad forecasts may result.
Finally, much has been made of prediction markets as effective forecasting models [13]. Market participants in prediction markets buy and sell contracts whose payoff is contingent on a particular event happening, such as a recession in the US by the end of 2008. Evidence suggests that such markets are well calibrated; if a contract is at 90%, then 9 times out of 10 that contract will pay out [10; 11]. Perhaps the way forward is to forecast using prediction markets [5] ?
Economic forecasts are widely used at the firm, industry, and economy-wide level. For a firm, economic forecasts facilitate planning for future production, expansion, or contraction. For example, a retailing firm that has been in business for the last 25 years may be interested in forecasting the likely sales volume for the coming year. Similarly, the auto industry may want to know the total demand for vans in the coming model year. Both production plans and the extent of competition in the automobile industry may depend on the magnitude of the forecasted auto demand. At the economy-wide level, one may want to know the economic forecast for growth in the real gross domestic product. One may also be interested in other macroeconomic variables such as the projected inflation rate. There are numerous techniques that can be used to generate economic forecasts [12].
While the term "economic forecast" may appear to be rather technical, planning for the future is a critical aspect of managing any organization—business, nonprofit, or other. In fact, the long-term success of any organization is closely tied to how well the management of the organization is able to foresee its future and to develop appropriate strategies to deal with likely future scenarios [6].
Intuition, good judgment, and an awareness of how well the economy is doing may give the manager of a business firm a rough idea (or "feeling") of what is likely to happen in the future. Nevertheless, it is not easy to convert a feeling about the future into a precise and useful number such as the next year's sales volume or the raw material cost per unit of output [7].
Suppose that a forecast expert has been asked to provide estimates of the sales volume for a particular product for the next four quarters. How should one go about preparing the quarterly sales volume forecasts? One will certainly want to review the actual sales data for the product in question for past periods. Suppose that the forecaster has access to actual sales data for each quarter over the 25-year period the firm has been in business. Using these historical data, the forecaster can identify the general level of sales. He or she can also determine whether there is a pattern or trend, such as an increase or decrease in sales volume over time. A further review of the data may reveal some type of seasonal pattern, such as peak sales occurring before a holiday. Thus
by reviewing historical data over time, the forecaster can often develop a good understanding of the previous pattern of sales. Understanding such a pattern can often lead to better forecasts of future sales of the product. In addition, if the forecaster is able to identify the factors that influence sales, historical data on these factors (or variables) can also be used to generate forecasts of future sales volumes [10].
There are many forecasting techniques available to assist in business planning. All forecasting methods can be divided into two broad categories: qualitative and quantitative. Many forecasting techniques use past or historical data in form of time series. A time series is simply a set of observations measured at successive points in time or over successive periods of time. Forecasts essentially provide future values of the time series on a specific variable such as sales volume. Division of forecasting methods into qualitative and quantitative categories is based on the availability of historical time series data [8].
When historical data are not available, qualitative forecasting techniques are used. Such techniques generally employ the judgment of experts in the appropriate field to generate forecasts. Quantitative forecasting methods are used when historical data on variables of interest are available—these methods are based on an analysis of historical data concerning the time series of the specific variable of interest and possibly other related time series [9].
There are two major categories of quantitative forecasting methods. The first type uses the past trend of a particular variable to base the future forecast of the variable. As this category of forecasting methods simply uses time series on past data of the variable that is being forecasted, these techniques are called time series methods. The second category of quantitative forecasting techniques also uses historical data. But in forecasting future values of a variable, the forecaster examines the cause-and-effect relationships of the variable with other relevant variables such as the level of consumer confidence, changes in consumers' disposable incomes, the interest rate at which consumers can finance their spending through borrowing, and the state of the economy represented, by such variables as the unemployment rate. Thus, this category of forecasting techniques uses past time series on many relevant variables to produce the forecast for the variable of interest. Forecasting techniques falling under this category are called causal methods, as the basis of such forecasting is the cause-and-effect relationship between the variable forecasted and other time series selected to help in generating the forecasts. Some economic forecasts are generated using a hybrid of the above two methods [9].
An important starting point in the forecasting process is the re-assessment of the economic climate in individual countries and the world economy as a whole. Here, a combination of model-based analyses and statistical indicator models play an important role in "setting the scene" at the start of each projection round.
A first step is to look at the range of relevant new information since the last projections were produced -
• Traditional (genetic) - a retrospective analysis of the actual number of requests for services and heuristi-cally identification of major trends that shape their future amount.
• Classic - prediction, given according to the limited number of dominant factors (usually - income and price);
• Modified - adaptation of the classical approach to the complex process of the formation of the modern demand for services [2].
This study is based on a modified approach, of forecasting the dynamics of the market. The study used the data of countries production grouped by geography (table 1), according to the data of World Steel Association [3,5]. Identified the following regions: The European Union (27), (10), CIS (7), North America (7) South America (9) Africa (l3), Middle East (7), Asia (16). Countries grouping into the regions can more accurately determine the market trend, while reducing the number of different trends existing in the national markets.
Table 1
Dynamics of production of steel in 2010, 2015 (tons) __
Region 2010 2011 2012 2013 2014 2015 Growth rate, %
EU 206903 210179 198229 139336 172777 177652 13,3
European countries (not members of the EU) 28205 30608 31710 29076 33734 39164 24,2
CIS 119906 124169 114345 97645 108200 112663 29,0
North America 131789 132618 124494 82578 111565 118893 13,5
South America 45298 48232 47354 37776 43894 48365 37,8
Africa 18695 18675 16970 15400 16624 15697 32,4
Middle East 15376 16452 16646 17656 20000 23002 29,5
Asia 674126 757285 783040 810346 916721 975614 49,4
World market production 1248991 1347002 1341212 1235827 1431664 1518299 28,0
such as changes in commodity prices (in particular the oil price), exchange rates and interest rates, fiscal trends, the path of economic activity and other key variables -to see how the recent past has developed differently from what was previously expected. With this new information, and using the previous set of projections as a starting point, the effects of the new elements and revised judgments are typically assessed on the basis of model simulations using the NIGEM global model and short-term indicator models. Thus the likely impact of combined and individual changes in assumptions and new information on key aggregates can be assessed in consistent fashion for each of the major economies and economic groupings. These results are mechanical and therefore intended to be no more than a guide to the informed judgments of country and topic experts on the underlying "forces acting".
Is generally distinguished three major campaign to methods of forecasting the market dynamics:
The purpose of this analysis is to identify regions that are expected to increase demand for steel, the duration of this dynamic and factors affecting it. Another purpose is the definition of the regions that are building their own production capacities to displace foreign manufacturer. In addition there is a necessity of determination a period when, regions - importers will turn into regions - exporters. The input data used for the analysis of
production volumes, level of consumption and GDP data for the consumer ability at current prices in U.S. dollars, steel consumption per capita.
GDP data (table 2) were used to determine the overall economic trends, operating in the world. Has been revealed the dependence between production and GDP's growth is the usage of steel in all sectors of the economy.
Table 2
The dynamics of GDP in purchasing power parity. (in current prices bill. $US)
Region 2010 2011 2012 2013 2014 2015 Growth rate, %
EU 13717 14587 14992 14490 14987 15542 -14,1
European countries ( not members of the EU) 1560 1675 1734 1685 1802 1938 38,9
CIS 2635 2953 3179 2991 3176 3400 -6,0
North America 16049 16855 17209 16785 17472 18209 -9,8
South America 3301 3631 3913 3939 4257 4550 6,8
Africa 1708 1858 1991 2065 2191 2262 -16,0
Middle East 1841 2000 2116 2180 2333 2384 49,6
Asia 17729 19824 21334 22286 24510 26492 44,7
World market production 61705 66835 70140 70154 74684 78970 21,6
Analysis of the dependence of steel of GDP shows that the world's steel production volumes are correlated with GDP. The study showed that the dependence of global steel production of the GDP by the equation y = 17,281 x + 136 610, where X is the world's GDP, with the magnitude squared R2 = 0,9431, indicating high distress communications.
In terms of regions, the most intimate connection GDP-production observed in the following regions:
Europe y = 21,421 x - 4850,3; R2 = 0,957., Asia y = 40,407 x - 74,492; R2 = 0,9873., Middle East y = 7,2417 x + 2927,5; R2 = 0,8431. These dependences show that in the world there is a steady growth of GDP, which stimulates the growth of steel production. The world average GDP growth of 17.281 billions $US provides production growth of 1 000 tonnes.
There is almost no dependence of GDP-production in the EU y = -3,7064 x + 238 796; R2 = 0,0771, CIS y = 3,9018 x + 101 131; R2 = 0,0728, South America y = 1,2343 x + 40,237; R2 = 0,0765, Africa y = =-0,337 x + 17,477; R2 = 0,0105.
To clarify the reasons for the lack of correlation in the EU, CIS, South and North America and Africa we consider the consumption of finished steel products in these regions, per capita. This indicator is the most accurate reflection of level of usage of steel in the country's economy, showing the population's production industry. In the more developed regions of the world: North America, the EU, which was consumed from 2002 to 2015, an average of 264.57 and 338.5 kg / capita, the highest number per capita were consumed in the UAE in 2008. 2210.9 kg / capita. According to the study, the growth of GDP and production was observed in regions of the world, which, since 2002. steel consumption population far below the consumption of the more developed regions: the EU and North America, but high growth (GDP growth 2002-2015. European countries, 73.3%, Middle East 89.8%, Asia -116%) stimulated the growth of domestic demand in the region, which in turn led to a significant increase production in the regions, what we are seeing in Asia, Europe, the Middle East.
Table 3
Forecasting of GDP growth in 2017 - 2019
Country\Year 2017 2018 2019
European countries 2301,79 2425,61 2562,78
Middle East 2830,58 2982,75 3151,95
Asia 35452,59 38431,51 41785,65
World market 97254,45 103479,8 110405,4
Table 4
Forecasting of steel production in the regions of the worlds in 2017 - 2019
Country\Year 2017 2018 2019
European countries 44456,34 47108,69 50047,01
Middle East 23425,71 24527,68 25752,98
Asia 1358041 1478410 1613941
World market 1817264 1924845 2044525
In most developed countries: EU, USA, Canada, Japan, South Korea, where over the study period, GDP per capita was high, there were only the fluctuations of consumption goods sector, depending on the economic situation in the region. Consumption data in these regions are used as the upper limit, above which the growth of GDP is no longer a significant impact on production and consumption in the region. Continuing the trend in production capacity in the region will need to search for sharp market outlets, which will make the competition Ukrainian steel industry. As for the countries of South America and Africa, they share low levels of production and consumption, in the absence of significant growth trends. For the CIS market is inherent high prevalence of production over domestic demand, which forces seek foreign markets, at the same time, domestic consumption is almost not developed (201kg/ capita) and much lower than the neighboring countries of Europe (252kg/ capita)
According to the data analysis of the dependence of production and GDP, and consumption of steel per person construct a forecast of production (Table 4). The input data used in the GDP data from the International Monetary Fund (Table 3).
The projections show that by 2017, the Asian per capita consumption over and above the EU average for 2002-2015, after which it is possible to expect reduction of growth rates in the region. In Europe and the Middle East, this boundary if the current trends will be achieved by 2018.
Conclusions. Middle East, and Europe until 2017, taking into account the general economic trends and market demand for the products of the metallurgical industry end users. Improving the effectiveness of forecasting the metallurgical industry allows advance rebuild production requirements demand. Improving forecasting technique allows regional competition increases the level of information security management, which positively affects the quality of the developed measures to reduce the risks of competition. According to the forecast, in the preservation of current economic trends, it is necessary to expect a 2017 2018godu, the saturation of domestic demand steelmakers in Asia, Europe and the Middle East. Projected domestic production, in which a saturation of the market for Europe is 50,047 tons, the Middle East 25,752.98 tonnes, 1,613,941 tonnes of Asia.
References
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Гончар В. В. Прогнозування як метод маркетингового дослщження ринку металопродукцп
Визначено проблеми прогнозування динамши розвитку металургшного ринку, попиту та пропози-ци на пiдставi загальноекономiчних тенденцш. Ви-сока експортна залежнють металурпйно! галузi Ук-ра!ни зумовила необхвднють вивчення тенденцш, дь ючих на свiтовому ринку, i визначення потенцiйних джерел конкуренцп в майбутньому. Проведено ана-лiз iснуючих динамiк, характерних металургiйному ринку регюшв свiту, оцiнено тенденцii розвитку, ди-намiку обсягiв виробництва. Для проведения ана-лiзу свiтовий ринок роздшений на 8 регiоиiв: Азгя, СС, Свропа, СНД, Близький Схвд, Африка, Пiвнiчна i Пiвденна Америка. Застосовано модифшовану методику прогнозування ринку на основi даних ВВП мiжнародного валютного фонду в крашах свiту та обсягiв виробництва сталi в крашах свiту згiдно даних мiжнародноi асоцiацii виробиикiв CTrni з 2002 по 2015 рш. Результати проведеного дослiджеиня дозволили видшити тюну кореляцiю мiж ВВП та об-сягом виплавки сталi в свт, крашах Азii, Близького Сходу та Свропи. Проведено аналiз споживання продукцii металургiйноi галузi, на основi якого ви-дiлено регiоии - лвдери споживання i аутсайдери. Споживання на душу населення в розвинених краь нах Свропейського Союзу дозволило визначити гра-ничний попит на продукщю галузi для розвинено1' економши. На основi даних дослiджеиь побудовано прогноз виробництва в свт i в крашах Близького Сходу, Азп, Свропи.
Ключовi слова: маркетииговi до^дження, прогнозування, споживачi сталi, металопродукцгя, ВВП.
Гончар В. В. Прогнозирование как метод маркетингового исследования рынка металлопродукции
Определены проблемы прогнозирования динамики развития металлургического рынка, спроса и предложения на основании общеэкономических тенденций. Высокая экспортная зависимость металлургической отрасли Украины обусловила необходимость изучения тенденций, действующих на ми-
ровом рынке, и определения потенциальных источников конкуренции в будущем. Проведен анализ существующих динамик, характерных металлургическому рынку регионов мира, оценены тенденции развития, динамика объемов производства. Для проведения анализа мировой рынок разделен на 8 регионов: Азия, ЕС, Европа, СНГ, Ближний Восток, Африка, Северная и Южная Америка. Применена модифицированная методика прогнозирования рынка на основе данных ВВП международного валютного фонда в странах мира и объемов производства стали в странах мира согласно данных международной ассоциации производителей стали с 2002 по 2015 год. Результаты проведенного исследования позволили выделить тесную корреляцию ВВП - объем выплавки стали в мире, странах Азии, Ближнего Востока и Европы. Проведен анализ потребления продукции металлургической отрасли, на основе которого выделены регионы - лидеры потребления и аутсайдеры. Потребление на душу населения в развитых странах Европейского Союза позволило определить граничный спрос на продукцию отрасли для развитой экономики. На основе данных исследований построен прогноз производства в мире и в странах Ближнего Востока, Азии, Европы.
Ключевые слова: маркетинговые исследования, прогнозирование, потребители стали, металлопродукция, ВВП.
Gonchar V. Forecasting as a method of metals marketing research
The problem of predicting the dynamics of the steel market, demand and supply on the basis of general economic trends is defined. High export dependence metallurgical industry in Ukraine led to the need to examine current trends in the world market, and identify potential sources of competition in the future. The analysis of existing speaker characteristic steel markets in different regions of the world is held. For analysis of the world market is divided into 8 regions: Asia, EU, Europe, CIS, Middle East, Africa, North and South America. The productions dynamics trends are evaluated. The modified method of forecasting the market is applied, based on data from the International Monetary Fund, GDP in the world and in steel production according to data from the International Steel Association from 2002 to 2015. The research results identified a close correlation of GDP and steel production volume in the world, Asia, the Middle East and Europe. The regions leaders and outsiders are distinguished after metallurgical production consumption analysis in the world. The demand level of the advanced economy was defined by the consumption per capita in developed countries of European Union. Based on these research, the production forecast is built in the world and in the Middle East, Asia, and Europe.
Keywords: marketing research, forecasting, steel consumers, steel, GDP.
Received by the editors: 17.10.2016
and final form 28.12.2016
