Tag: job creation

Creative Industries: Impact on the Development of Ukraine’s Economy

Image of coloured umbrellas representing impact of creative industries

This brief is based on research investigating the effects of creative industries on the development of the Ukrainian economy. The results indicate that capital investment in creative industries has a significantly greater effect on economic growth than a simple increase in the consumption of the respective industry’s products. Thus, we conclude that to achieve a more substantial economic effect of spending in creative industries, it is necessary not only to increase the expenditures in these industries and boost consumption of their products but also to support these industries in developing production capacity. The underlying study “Creative Industries: Impact on the Development of Ukraine’s Economy” was prepared by the Kyiv School of Economics in cooperation with the Ministry of Culture and Information Policy of Ukraine. The first results from the study were presented at the international forum “Creative Ukraine” in 2020.


In 2019, the United Nations (UN) General Assembly declared 2021 as the International Year of Creative Economy for Sustainable Development. This nomination was a recognition of the growing role of creative industries in the economic development of both developed and developing countries. The program of events taking place under the theme of the International Year of the Creative Economy for Sustainable Development includes forums, conferences, and intergovernmental meetings, which intend to draw attention to the problems that hinder the development of creative industries (CI) and the opportunities that these areas create.

The importance of CIs, which lie at the crossroads of art, business, and technology, is constantly growing both at the national level and in terms of international competition between countries. CIs have become a strategic direction for increasing competitiveness, productivity, employment, and sustainable economic growth (UNCTAD 2019) [1]. Exceptional rates of growth in turnover, creation of new jobs, and resilience to the economic crisis make creative industries an attractive area for investment at both the private and governmental levels. (UNCTAD 2004) [2]. On the other hand, the scope of knowledge about the economic role of CIs and their impact on the development of other sectors of the economy is quite limited.

This brief describes the economic effect of spending in CIs. Particularly, using input-output and computable general equilibrium models, we outline CI multiplier effects on the development of other industries and discuss implications for government support of CI.

Creative Industries in Ukraine

Although the term creative industry is becoming more common, countries have different approaches to the definition. There have been attempts to introduce an international standard, but the goal has not yet been achieved [3].

Ukrainian law define CIs as “types of economic activity aimed at creating added value and jobs through cultural (artistic) and/or creative expression”.

Currently, the Cabinet Ministers of Ukraine list 34 basic economic activities belonging to CIs, including visual arts, performing arts, publishing, design, fashion, IT, audiovisual arts, architecture, advertising, libraries, archives and museums, folk arts and crafts.

The gross value added (GVA) of CIs in Ukraine is growing rapidly. In 2013, the GVA of creative industries amounted to UAH 31 billion (3% of total value added), and in 2019 it amounted to UAH 117.2 billion (3.9% of total value added) (Figure 1). The number of companies and employees in the field of CI is also growing rapidly. In 2019, there were 205.5 thousand business entities and more than 350 thousand employees. 

Figure 1. Gross value added of CI in Ukraine

Source: State Statistics Service of Ukraine

Most GVA of CIs is generated by information technology (IT) activities. In 2019, the IT sector generated UAH 63.7 billion of GVA or 54.3% of the national CI GVA (Figure 2). In second place, there is Advertising, ¢Marketing and PR – UAH 20.2 billion of GVA or 17% of national GVA. In third place with a small gap there is Audiovisual Art – UAH 19.4 billion of GVA or 17% of national GVA.

Figure 2. Structure of Gross Value Added CI in Ukraine, 2019.

Source: State Statistics Service of Ukraine

Methodology and Data

To assess the economic effect of creative industries, we employ a computable general equilibrium (CGE) approach. CGE estimates a general equilibrium model of an economy using real-life economic data. It models interactions of individual markets – such as manufactured goods, services, and factors of production – encompassing the entire economic system. In doing so, the model takes into account reactions of economic agents – economic sectors, households, government, external sectors – and assumes that markets are perfectly competitive. The resulting set of simultaneous equations then employs real data from the economy in question to estimate the equilibrium in these markets by balancing supply and demand in all markets via the appropriate choice of prices.

In this way, the CGE model is a good reflection of a studied economy. In particular, in application to our research question, it allows us to distinguish the economic impact of additional consumption and capital investments in creative industries, and therefore to form reasonably precise recommendations for policy measures. This feature makes the CGE approach much more relevant than the alternative methods, such as the input-output approach.

Limitations of the CGE approach include increased analytical difficulty and computational demands, calibration and the use of estimated parameters, etc.

Data utilized by the CGE model are given by the Social Accounting Matrix (SAM). The SAM structure is related to the input-output table. Each row and column reflects the income and expenses of a particular economic agent. The main principle of SAM is balance, i.e., income from the sale of goods and services equals expenditures.

As a result, the availability of input-output table data is a crucial factor for our analysis. The State Statistics Service of Ukraine publishes an input-output table for 42 industries, which is not sufficient to distinguish creative industries from other sectors of the economy. To compensate for these deficiencies, we use the following sources:

  • input-output table for Ukraine for 2018.
  • input-output table for Poland for 2015 (latest available) to approximate the intermediate consumption of creative industries, not available from Ukrainian input-output tables.
  • annual report on state budget expenditures of Ukraine for 2018.
  • balance of payments of Ukraine for 2018.
  • structural business statistics of Ukrainian enterprises in part of gross value added and sales volume for 2018.


The results of the CGE model suggest a strong effect of investment in CIs.  The sizes of the multipliers across the most creative industries are similar. The exception is the programming industry, for which for a one hryvnia investment leads to a total GDP growth of 3.2 hryvnias. This value is the highest among all sectors of the economy, not only among the CIs. For the rest of the CIs, the multiplier ranges from 1.9-2.2, which is comparable to the multipliers of the construction and finance and insurance sector (Figure 3). Accordingly, the increase in GDP for one hryvnia of investment by the industry is:

  • UAH 2.2 for libraries, museums, archives.
  • UAH 2.1 for publishing.
  • UAH 2.1 for architecture.
  • UAH 2.0 for performing and other arts.
  • UAH 2.0 for production of jewellery, costume jewellery, musical instruments.
  • UAH 2.0 for public relations, marketing, advertising.
  • UAH 2.0 for design, photography, translation.
  • UAH 1.9 for audiovisual and audio art.

Figure 3. GDP change per one hryvnia of capital expenditures*

* Estimated assuming 5% increase in capital Source: Our calculations are based on data from State Statistics Service of Ukraine and Poland, as described in the data section.

While the above results are obtained by estimating GDP response to a 5% increase in capital, the results are quite similar for different sizes of investments.


Our estimations show that investment in creative industries has a considerable impact on GDP. Investment in the IT sector has the highest multiplier, even compared to “non-creative” sectors of the economy. Other CIs’ multipliers can be compared to the construction and finance and insurance sector. Therefore, the results suggest that creative industries offer a highly valuable investment opportunity.

We also find that increase in capital investment in a creative industry has a stronger positive impact on GDP than an increase in the consumption of the respective industry’s products. An immediate policy implication of this finding is that, to achieve a more significant economic effect of government spending in creative industries, it is necessary not only to increase the expenditures on these industries or boost consumption of their products but also to support them in expanding production capacity.


  • Nikolaeva, O., Onoprienko, A., Taran, S., Sholomitskyi, Y. and Iavorskyi, P., 2020. Creative Industries: Impact on the Development of Ukraine’s Economy. Ministry of Culture and Information Policy of Ukraine.
  • UNCTAD, 2019. How can the creative economy help power development? https://unctad.org/news/how-creative-economy-can-help-power-development
  • UNCTAD, 2004. Creative Industries and Development. https://unctad.org/system/files/official-document/tdxibpd13_en.pdf

 Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

The Effect of Municipal Strategic Planning on Urban Growth in Ukraine

FREE Network Policy Brief | Between East and West: Regional Trade Policy for Ukraine

Authors: Denys Nizalov and Olena NizalovaKEI.

In a downturn, the pressure is especially high on governments to produce sensible and effective development strategies to generate needed jobs and increased earnings. A large number of economic development tools were used in the past by local and national governments around the world, designed to facilitate regional and local economic growth. This brief presents the preliminary results from the evaluation of a program implemented in Ukraine.

Bradshaw and Blakely (1999) distinguish three historical waves of popularity for different tools used in economic development, with reference to the US states’ development policy:

  • 1st wave – Incentive-based competition for industrial location, so called smokestack chasing (direct incentives to firms, reimbursement of relocation and infrastructure costs, tax-breaks);
  • 2nd wave, from the early 80s – Cost-benefit-based assistance, focusing on internal growth (business incubators, start-up funds, trainings);
  • 3rd wave, over the last two decades – Building of a “soft infrastructure” (institutions) conducive to economic growth (strategic planning, marketing, public-private partnerships, financing, regulation, intergovernmental collaboration).

While the effect of the first two waves on various growth outcomes was studied extensively (for reviews, see Bartik 1991; Fisher 1997; Wasylenko 1997; Goss and Phillips 1999; Buss 2001) the effect of the policies representing the third wave is less known. There are several reasons for that. These policies were developed relatively recently, they are hard to measure and compare and are most likely to have a long run effect.

A unique example of a third-wave policy was recently evaluated in Ukraine. The Local Economic Development (LED) Project in Ukraine, started by the USAID in 2004, introduced a process of municipal strategic planning into the practice of local government decision making. This Strategic Planning process involves setting goals and priorities for community economic development and coordination of activities in different areas of community life. It also allows the establishment of partnerships among various stakeholders and interest groups, and the mobilization of public and private resources to facilitate economic development.

Until recently, the effect of municipal strategic planning has been assessed exclusively by case-studies. See for example, the cases of Randstad (Priemus, 1994), Lisbon (Alden and Pires, 1996), London (Newman and Thornley, 1997), Hong Kong (Jessop and Sum, 2000), Guangzhou (Li, Yeung, Seabrooke, 2005; Wu and Zhang, 2007), and Hangzhou (Wu and Zhang, 2007). Although the above mentioned cases describe the planning process and the perceived benefits in great detail, they do not address the question of whether the Strategic Planning causes a higher rate of community economic growth or not. There are several reasons for these limitations. The procedure of planning, beyond general similarities, differs greatly in the implementation details from case to case, which makes any comparisons complicated. Moreover, the decision to start the planning process in those cases is thought to be endogenous since cities that are more likely to benefit from strategic planning are also more likely to get involved in this.

The LED example is much more suitable for evaluation. The implementation of the strategic planning system in the participating cities has been performed using a standardized procedure with the help of LED advisors. With one exception, the implementation took from 4 to 12 months. Also, the selection of the participating cities was done by LED personnel based on clear participation rules. Altogether, the LED activities targeted the same goal in each city – FDI growth and creation of new jobs. Moreover, a relatively large number of communities – 74 cities from all regions of Ukraine – were involved in the project by mid-2008.

Internal reports point to a great success of the project. More than 30 cities had by mid-2008 reported an increase in FDI. Collectively, the partner cities reported $700 million of inflowing investment and an addition of about 12,000 jobs.

The impact of the LED project on the following outcomes was evaluated using more rigorous statistical procedures:

  • Number of businesses per capita;
  • Fixed capital investment per capita;
  • Number of jobs per capita;
  • Unemployment rate; and
  • FDI per capita.

It was found that the LED project had a positive overall effect on the number of businesses, fixed capital investment, and the number of jobs. In absolute values, the introduction of strategic planning lead to 6 to 12 new jobs per 1,000 of population, 18 to 50 new businesses per 100,000 of population, and 5 to7 million USD of investments in fixed capital per 100,000 (controlling for other factors of influence). However, differences in the project effect among the cities were found. The reasons for these differences in impact include:

  • the effect was observed at different points of time after the implementation of planning (1 to 45 month by Dec. 2008);
  • the cities had different implementation teams (composed of 6 advisors); and
  • the municipalities had different administrative subordination (58 cities and 16 small towns of rayon subordination);

The project effects on the number of businesses, fixed capital investment, number of jobs, and the unemployment rate increased each month. The administrative subordination affects only the effectiveness of investments and job creation: the effect is larger for cities than for rural towns. Team-specific differences are evident on all outcomes. This confirms that the implementation have a significant impact on the success of this intervention.

Finally, the effect of LED was compared to the effect of a similar project implemented in Ukraine by UNDP. Provided that the results presented above are robust, it turns out that the effects of the two projects introducing strategic planning are very similar in magnitude and significance.


  • Bartik, T.J., 1991. Who Benefits from State and Local Economic Development Policies? Upjohn Institute for Employment Research: Kalamazoo, MI.
  • Buss, T.F., 2001. “The Effect of State Tax Incentives on Economic Growth and Firm Location Decisions: An Overview of the Literature,” Economic Development Quarterly 15(1), 90-105.
  • Fisher, R.C., 1997. “The Effect of State and Local Public Services on Economic Development,” New England Economic Review March/April, 53-67.
  • Goss, E. and J. Phillips, 1999. “Do Business Tax Incentives Contribute to a Divergence in Economic Growth?” Economic Development Quarterly 13(3), 217-228.
  • Wasylenko, M., 1997. “Taxation and Economic Development,” New England Economic Review March/April, 37-52.