The winner takes it all? Multidimensional assessment of economic growth factors in Bundesländer

Gotz, Marta Article The winner takes it all? Multidimensional assessment of economic growth factors in Bundeslander Comparative Economic Research. Central and Eastern Europe Provided in Cooperation with: Institute of Economics, University of Łódź Suggested Citation: Gotz, Marta (2010) : The winner takes it all? Multidimensional assessment of economic growth factors in Bundeslander, Comparative Economic Research. Central and Eastern Europe, ISSN 2082-6737, Łodz University Press, Łodz, Vol. 13, Iss. 3, pp. 141-161, https://doi.org/10.2478/v10103-009-0042-3 This Version is available at: https://hdl.handle.net/10419/259049 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/4.0 10.2478/v10103-009-0042-3 MARTA GÖTZ ∗ ∗∗ ∗ The winner takes it all ? Multidimensional assessment of economic growth factors in Bundesländer Abstract This paper seeks to offer a thorough assessment of current state of the play as well as developments taking place in 1989-2008 with respect to various determinants of economic growth in Germany. The primary aim is to evaluate the growth potential by constructing and consequently calculating the summary index encompassing various dimensions of economy. In order to take a holistic and comprehensive view on economic growth factors, conceptual framework of five modules encapsulating numerous factors and thus incorporating various growth aspects has been put forward. Competitiveness (production function), Sectors (output approach), Business cycle (expenditure approach), General economic condition (main macroindices) and Catalysts (residual - all other factors) are taken into account. Preliminary results confirm to some extent earlier studies pointing to existing West-East Germany’s discrepancies. It seems particularly visible when taking into account elements of the first module and - key for long term growth - factors of the fifth unit. 1. Introduction Germany's reunification offers an unique research laboratory. Fall of the Berlin Wall and subsequent unification of previously divided BRD and DDR ∗ Ph. D., Institute for Western Affairs in Poznań 142 Marta Götz can be regarded as a special type of EU enlargement and an example of EU integration (Neal, 2007: 201-229). Right from the start public opinion and policy makers were optimistic about speedy "knitting together" of two artificially separated countries. Against the background of expectations ignited in early 1990s, deliveries might be assessed as somewhat mediocre (Ragnitz, Scharfe, Schwirtz, 2009). Though, one has to remember the humble beginnings of DDR economy in united Germany. Obsolete infrastructure, hidden unemployment, dominance of state ownership, and other - shared by so many Eastern and Central Europe Economies – deficiencies (Paque, 2009). Germany’s economy continues to be perceived by many as the "tale of two countries". This paper seeks to offer a thorough assessment of current state of the play as well as developments taking place in 1989-2008 with respect to various determinants of economic growth in Germany. The primary aim is to evaluate the growth potential by constructing and consequently calculating the summary index encompassing various dimensions of economy. Research and assessment process is reflected in paper's sections. The first one setting the stage outlines the main inspirations influencing the index creations and the whole methodological process. The next one describes methodology and sources used in calculations. It also briefly sketches the main stylized facts of German economy with respect to selected modules. Third part details the sequences of creating summary index. Some possible advantages are listed next. The last sections discuses results obtained and draws some general tentative conclusions. 2. Inspiration • The idea of constructing following index was inspired mainly by three wellknown indices. • Bundesländerranking established by Neue Soziale Marktwirtschaft (INSM) evaluating both current growth potential as measured in 5 dimensions: labour market, enterprises, economic structure, regional attractiveness and welfare and dynamic expressed in terms of changes in these selected areas (http://www.bundeslaenderranking.de/methodik.html accessed 02.11.2009). • Global Competitiveness Index (GCI) by World Economic Forum (Geneva) encompassing 12 pillars and grouping countries according to their main competitiveness’s drivers in one of three distinguished groups: factor driven; efficiency driven or innovation driven (Sala-i-Martin, 2009). Elements taken into account include: institutions, infrastructure, macroeconomic stability, The winner takes it all?… 143 health and primary education, higher education and training, goods market efficiency, labor market efficiency, financial market sophistication, technological readiness, market size, business sophistication and innovation. The actual construction of GCI involves the aggregation of the 12 pillars into a single index, measures are reported for the 12 pillars separately offering a more disaggregated analysis useful to countries and practitioners. The hard data indicators used in the GCI are normalized on a 1-to-7 scale (in order to align them with the Executive Opinion Survey’s results). The computation of the GCI is based on successive aggregations of scores, from the lowest level all the way up to the overall GCI score (i.e., the highest level), using the weights. • European Innovation Scoreboard – up until 2009 overall innovation performance was calculated on the basis of 25 indicators covering five dimensions of innovation: innovation drivers measuring the structural conditions required for innovation potential; knowledge creation measuring the investments in R&D activities; innovation & entrepreneurship measuring the efforts towards innovation at the firm level; applications measuring the performance expressed in terms of labour and business activities and their value added in innovative sectors; and intellectual property measuring the achieved results in terms of successful know-how (European Innovation Scoreboard 2007). For the EIS 2008-2010, the number of dimensions will be increased to 7 and grouped into 3 main blocks of dimensions (Hollanders, Tarantola, Loschky, 2009). The purpose of this revision is to have dimensions that bring together a set of related indicators in order to give a balanced assessment of the innovation performance in that dimension. The blocks and dimensions have been designed to accommodate the diversity of different innovation processes. 3. Methodology Following steps have been undertaken in order to calculate a synthetic index. 1. Creation of conceptual scaffolding synthesizing various growth determinants. Five (I-V) modules have been distinguished, each encompasses specific factors contributing directly or indirectly to economic growth. 2. Selection of indicators being proxies of distinguished categories within pillars I-V. 144 Marta Götz 3. Analysis of current situation as well as of changes happening so far in each category based on available statistics. Figures have been retrived from databases of 16 Bundesländer provided by Volskwirtschaftliche Gesamtrechnungen der Länder VRGL Destatis, years 1989-2008. 4. Estimation of partial indices by the way of including both current levels as well as earlier decreases/ increases and subsequently assigning weights to all factors 5. Calculation of summary index of growth potential (SG). The intention was to take a holistic and comprehensive view on economic growth factors, accommodating both business and political dimensions prevailing in media with scientific approach drawing on specific methodology (Hausmann, Klinger, Wagner, 2008: 2). A conceptual framework - “navigation tool” - incorporating various aspects enabling analysis of economic growth factors has been put forward. Creating conceptual scaffolding synthesizing yet differentiating among various growth determinants was the first step of such endeavor. Table 1. Outline of proposed conceptual framework Pillars / modules I Competitiven ess II Sectors (“output approach”) III Business cycle (“expenditure approach”) IV General economic condition (“macroecono mic stabilization pentagon”) V Catalysts (all other factors) Factors to be taken into account Basic elements as in production function: capital, labor, total factor productivity (TFP) Traditional approach distinguishing: Agriculture Industry Services Components of macroeconomi c equation: export/import, government expenditures, investment, consumption Inflation Unemployment GDP growth Current account deficit Fiscal stability R&D human capital entrepreneur ship SMEs Source: Own elaboration. The winner takes it all?… 145 Each of the pillars looks at growth determinants from different perspective. I. First module refers to macroeconomic production function and growth accounting, as well as analyses of European Union datasets AMECO, German "wise men" Sachverständigenrat (Sachverständigenrat Jahresgutachten 2007/2008: 443), Project KLEMS (Timmer, O’Mahony, van Ark, 2007), and OECD. As it is believed, the source of modern growth are predominately TFP and ICT investments. Stylized facts about Germany indicate however, certain deficiencies in this respect and still significant negative impact of labour factor (Mc Morrow, Roeger, 2007: 83; Eicher, Strobel, 2008: 39; OECD 2009). II. Second pillar reflects the contributions of various sectors to global production. It refers not only to traditional agriculture, industry and services, but also high or low tech industries; or division of ICT producing versus ICT using branches. Stylized facts about Germany point to: relative importance of ICT producing rather that more valuable ICT using branches and that construction boost soon after reunification has not been so far compensated by another, well performing though rare cleantech (Eicher, Strobel, 2009). III. Third module stands for basic components of business cycles variables included in fundamental macroeconomics equation (Sinn, 2008). Seen this way, German’s economy reveals strengths as well as weaknesses – impressive exports values, mediocre investments volumes and persistent low domestic consumption (Rebalancing the world economy: Germany The lives of others, The Economist, 2009). IV. Fourth pillar encompasses basic figures describing how fit the economy is. It draws on more indirect factors of economic growth - peaks (prongs) of so called magic economic pentagon (Misala, 2007). Data confirm, Germany performs well in terms of current account deficit thanks to export phenomenal results or inflation. Unemployment levels as well as budget growing deficits are however matter of concern (20 Jahre Deutsche Einheit – Rückblick und Ausblick, IWH Halle, 2009: 90). V. Last but not least, fifth module being of residual character encompasses all other factors not included in I-IV pillars affecting growth more indirectly, rather in the long run, though not necessarily. Elements such as R&D expenditures, education quality, clusters, SMEs, taxes, etc. can be taken into account. According to latest EU Innovation Scoreboard Germany belongs to top three innovative EU members – following Sweden and Finland (European Innovation, Scoreboard (EIS) 2009). 146 Marta Götz Selection of the most appropriate variables has been hampered by data availability at regional level. Due to this limitations (e.g. no growth accounting statistics for regional level) following indices have been singled out as proxies of variables mentioned earlier: I. productivity (GDP per worker); employment (head counts), working hours (million hours in Bundesland), II. value added in agriculture, industry and services, III. export, domestic consumption, public expenditures, investments, IV. unemployment rate, inflation, current account balance (differences export and import), budget deficit or surplus, GDP growth rate, V. R&D expenditures, patent applications, employment in knowledge intensive sectors and population of students. 4. Procedure Heading for synthetic (encompassing I-V units) and dynamic (including both current levels and changes recorded between years 1989-2008) indicator the first step was to rank Bundesländer in ascending order, from the worst in a given category to the best one (i.e. from the one with highest inflation rate, unemployment or lowest GDP growth to the one with highest GDP growth, lowest unemployment and inflation levels) in both current values and in terms of changes happened when comparing the last and first years of analysis. With the exception of deficits - current account or public finance, debt level or inflation and unemployment, increases in all remaining categories have been regarded as positive development. However, interpretation of public spending (government expenditures) may raise some doubts (Rzońca 2005; Krawczyk 2009). For depending on the perspective taken (long versus short run) or type (structural rigid social transfers or R&D expenditures) the increases may in fact indicate positive as well as negative changes. In this study raising values has been regarded as favorable development. Next, the best performer (Bundesland with best scores) has been defined as the reference point. This enables assigning value of all other units by relating their respective first hand figures to the levels of best performers. Weights have been ascribed to all factors based on the literature The winner takes it all?… 147 review, so they have discretional (arbitrary chosen) character 1 . Fractions of 1 attached to selected variables shall reflect certain “stylized facts” linked with them. Following weights have been ascertained 2 : I. Productivity; employment, and working hours each has got 0,3. Equal distribution of weights reflect the ambiguity of German economy – one the one hand it is TFP which is supposed to be the key driver of growth in highly developed countries (Eicher, Strobel, 2008: 39; Eicher, Strobel 2009: 17), on the other hand it is labour input which keeps negatively and strongly influencing economic growth in Germany (Niemcy szykują się na najgorsze, Rzeczpospolita, 2009). II. Since in the post-industrial, service economies, as the name indicates, services play decisive role for growth following weight have been assigned: value added in agriculture – 0,1, industry – 0,4 and services – 0,5 (Gramke 2007: 11). III. The total value of weight one has been divided in a following way to give account of the role played by four elements of global demand: 0,4 for export (Garbicz 2008, 260) since it reflects country’s competitiveness and do not restrict economy to domestic market; 0,3 for investment (Back above the bar again, The Economist, 2007; Rebalancing the world economy: Germany The lives of others, The Economist, 2009) crucial in the long run, however in Germany lagging behind as a result of lack of interesting opportunities to invest money home instead of transferring it abroad; 0,2 for domestic consumption (Rebalancing the world economy: Germany The lives of others, The Economist, 2009; Short work of it, Financial Times, 2009) permanently dubbed as Achilles’ heel of German economy reflecting traditional societal inclination for savings; and 0,1 for government expenditures (Siebert 2006, 10) since in Germany it unfortunately stands mainly for social transfers rather than so needed R&D expenditures or innovation support. 1 For instance for Global Competitiveness Index to obtain the precise weights, a maximum likelihood regression of GDP per capita was run against each subindex for past years, allowing for different coefficients for each stage of development. The Global Competitiveness Report 2009– 2010; World Economic Forum Geneva, Switzerland 2009; Xavier Sala-i-Martin. 2 *if there are some particular information missing for a given Bundesland weights for partial indices have been modified – for instance lack of data on inflation rate resulted in only four instead of five elements taken into account thus 4*0,25 and not 5*0,2. 148 Marta Götz IV. Due to heterogonous character of this module all elements namely: unemployment rate, inflation, current account balance, budget deficit or surplus, and GDP growth rate have been ascribed the value of 0,2. V. Since the literature review does not give any clear cut basis as to which factor shall be recognized as the most important one, similarly all factors within fifth module: R&D expenditures, patent applications, employment in knowledge intensive services and population of students have been described as equally important and given equal values of 0,25. They all influence social capital and innovativeness – key determinants for future growth. 6. Prospect advantages Proposed summary index seems to have an all embracing character and thus offering a comprehensive view on growth potential. • It takes into account various aspects of growth: long / short run, direct / indirect influence. • It reflects current levels and recent developments (reveals similarity to Neue Social Market Inititave Bundesländerranking including both Bestandsranking and Dynamikranking). • It refers to absolute values (import, export) and relative ones (inflation rate, productivity per employee) which on the one hand shows where exactly (in which Land) the real potential of Germany resides and on the other hand rank Bundesländer allowing for more precise and comparable estimates (for instance not biased due to population size). Obviously, it reveals some shortcomings these however may be presumably reflect the broader weaknesses of any rankings or synthetic indices (Hausmann, Klinger, Wagner, 2008: 11; Heilemann, Lehmann, Ragnitz, 2006). Formula for summary index of growth potential is following one (average of five modules): SG = (I+II+III+IV+V)/5 Theoretically, the maximum value of SG is 1. It can be obtained by the Bundesländer if it scores in all categories maximum = 1. Minimum, however, standing for the bottom of ranking cannot be defined apriori since it depends on values ascribed in first step (in relation to the first top region). The winner takes it all?… 155 Figure 7. Sectors – output approach (II) The Top Three NW BY TH 0,58 0,56 0,48 Source: Own calculations based on VRGL data. Figure 8. Business cycle - “expenditure approach” (III) 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 BW BY BE BB HB HH HE MV NI NW RP SL SN ST SH TH The Top Three BY NW BW 0,62 0,61 0,53 Source: Own calculations based on VRGL data. 0 0,1 0,2 0,3 0,4 0,5 0,6 BW BY BE BB HB HH HE MV NI NW RP SL SN ST SH TH 156 Marta Götz Figure 9. General economic condition - “magic macroeconomic pentagon” (IV) The Top Three SL BY RP 0,62 0,59 0,57 Source: Own calculations based on VRGL data. Figure 10. Catalysts - all other factors (V) The Top Three BW BY NW 0,69 0,59 0,42 Source: Own calculations based on VRGL data. The synthetic value of growth potential as measured by SG is depicted on the graph below. 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 BW BY BE BB HB HH HE MV NI NW RP SL SN ST SH TH -0,1 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 BW BY BE BB HB HH HE MV NI NW RP SL SN ST SH TH The winner takes it all?… 157 Figure 11. Values of synthetic index for each Federal State Source: Own calculations based on VRGL data. Totally, Bayer achieved highest value of the synthetic index SG and shows highest economic growth potential followed by Baden Württemberg and Nordrhein Westfalen. Results obtained confirm to some extent earlier studies pointing to existing West-East Germany’s discrepancies. It is particularly visible when taking into account elements of the first module and key for long term growth factors of fifth pillar. 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 BW BY BE BB HB HH HE MV NI NW RP SL SN ST SH TH 158 Marta Götz Figure 12. Federal States' performance in terms of I and V pillars Source: Own calculations based on VRGL data. There is a certain “leader monotony” in the results obtained. However, one must not ignore the achievements obtained and progress made by new Bundesländer as measured by positive time developments. 8. Conclusions Proposed index, calculated in this paper for Germany federal states, aims at offering a synthetic insight into any economy growth potential. Multidimensional yet simple it shall be developed in the future, so it might be applied for other countries. Possible improvements may include more frequent statistical figures (e.g. quarterly not annual) used for calculations. Weights shall be adjusted and customized for the economy under consideration since they reflect importance of certain factors for this country. Some refinements may be also needed for indicators selection. BW BY HB HH HE MV NI NW RP SL ST SH BE BB SN TH -0,1 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 -0,4 -0,2 0 0,2 0,4 0,6 0,8 I pillar V pillar The winner takes it all?… 159 20 years of German Reunification offers a good opportunity to take a stock of progress done so far, however the opinions in this respect differ significantly. Whereas J. Ragnitz from Ifo Dresden (2009) or H. Flassbeck from UN (2009) claim that East regions still need some special attention and assistance; U. Blum from IWH Halle (Aufbau Ost, IWH-Chef: Osten braucht keinen neuen Solidarpakt, 2009) and former member of Sachverständigerrat R. Pohl (2009) argue that such support is superfluous. Either because it's not working or because it has already fulfilled its role. More balanced view on this topic offer analysts from influential economic weekly Wirtschaftswoche (Schnaas 2009) or IW Köln (2009) according to whom the economic landscape of Germany does not any more fit into simple dichotomy East-West. Instead it s more subtle and reflects patchwork of prosperous and lagging behind regions scattered all over the country. Though Bayer and Baden Württemberg stands out clearly, such moderate approach seems most appropriate one when assessing economic growth potential in Germany. References 20 Jahre Mauerfall, Der Soli hat bald ausgedient, (2009), Institut der deutschen Wirtschaft Köln, Nr. 45/3. November 2009 Aufbau Ost, IWH-Chef: Osten braucht keinen neuen Solidarpakt, (2009), Wirtschaftswoche, 31.10.2009 Back above the bar again, (2007), ‘The Economist’, 12.07.2007 Bundesländerranking - http://www.bundeslaenderranking.de/methodik.html Das Produktionspotenzial in Deutschland: Ein Ansatz für die Mittelfristprognose, Das Erreichte nicht verspielen, Sachverständigenrat Jahresgutachten 2007/2008 Economic Policy Reforms: Going for Growth , OECD 2009 Eicher T., Strobel T. (2008), Der deutsche Produktivitätsabschwung: Ursachenforschung auf Branchenebene, Ifo Schnelldienst 15 Eicher T., Strobel T. (2009), Information Technology and Productivity Growth, German Trends and OECD Comparisons, Ifo Economic Policy, Edward Elgar, Cheltenham, UK, Northampton, MA, USA European Innovation Scoreboard 2007 comparative Analysis of Innovation Performance, European Commission, ProEurope Inno Paper no 6, Ferbuary 2008 European Innovation, Scoreboard (EIS) 2009, Comparative analysis of innovation performance, ProEurope Inno Paper no 15, March 2010 160 Marta Götz Flassbeck H. (2009), Wendezeit, „An jeder Ecke wurde gesprengt und gedüngt", Wirtschaftswoche, 08.11.2009 Garbicz, M. (2008), Rosnące nierówności dochodowe w Polsce po 1990 roku. Próba opisu mechanizmów. w W. Pacho, M. Garbicz (red.), Wzrost gospodarczy a bezrobocie i nierówności w podziale dochodu, SGH, Warszawa Gramke K. (2007), Globalization and the Labour Market in 2030, Prognos AG, Globalization and change, Bertelsmann Stiftung, Gütersloh Hausmann R., Klinger B., Wagner R., Doing growth diagnostics in practice: A „Mindbook”, CID Working Paper No. 77, Harvard University, September 2008 Heilemann U., Lehmann L., Ragnitz J. (2006), Länder-Rankings und internationale Wettbewerbsfähigkeit Eine kritische Analyse 2006, Nomos Verlag, 2006, Schriften des Instituts für Wirtschaftsforschung Halle, Band 24 Hollanders H., S. Tarantola, A. Loschky (2009), Regional Innovation Scoreboard 2009 - Methodology report, Pro Inno Europe, Brussels Krawczyk M. (2009), Deficyt budżetu państwa i aktywność gospodarcza, ‘Ekonomista’ nr 5 Mc Morrow K., Roeger W. (2007), An Analysis of EU Growth Trends, with a particular focus on Germany, France, Italy and the UK, National Institute Economic Review January 2007; no. 199; 82 Misala J. (2007), Stabilizacja makroekonomiczna w Polsce w okresie transformacji ze szczególnym uwzględnieniem deficytów bliźniaczych, Warszawa Neal, L. (2007), The Economics of Europe and the European Union, Cambridge Niemcy szykują się na najgorsze, (2009), Rzeczpospolita Paque, K. H. (2009), Die Bilanz, Eine wirtschaftliche Analyse der Deutschen Einheit, Hanser, München Pohl R. (2009), Wendezeit, „An jeder Ecke wurde gesprengt und gedüngt", Wirtschaftswoche, 08.11.2009 Ragnitz J., Scharfe S., Schwirtz B. (2009), Bestandsaufnahme der Wirtschaftlichen Fortschritte im Osten Deutschlands 1989-2008 Gutachten im Auftrag der INSM GmbH Köln, Dresden Juli 2009 Rebalancing the world economy: Germany The lives of others, (2009), The Economist, 07.08.2009 Rzońca A. (2005), Finanse publiczne a wzrost gospodarki w długim okresie. Analiza przy wykorzystaniu zmodyfikowanego modelu nabywania wiedzy przez praktykę, Materiały i Studia, Zeszyt nr 198, NBP, Warszawa Sala-i-Martin X. (eds.) (2009), Global Competitiveness Report 2009-2010, World Economic Forum, Geneva Schnaas D. (2009), 20 Jahre Mauerfall, Deutschland einig Flickenteppich, Wirtschaftswoche 09.11.2009 The winner takes it all?… 161 Siebert H. (2006), Old Europe’s social model – a reason of low growth? The case of Germany, Kiel Working Paper no. 1291, Kiel Institute for World Economics, Sinn H.W. (2008), Separate Dynamik, Wirtschaftswoche, 18.08.2008 Timmer M., O’Mahony M., van Ark B. (2007), EU KLEMS Growth and Productivity Accounts: Overview, November 2007 Release, official KLEMS project website Streszczenie ZWYCIĘZCA BIERZE WSZYSTKO? SYNTETYCZNA I WIELOASPEKTOWA OCENA CZYNNIKÓW WZROSTU W NIEMIECKICH KRAJACH ZWIĄZKOWYCH . Artykuł stara się dokonać kompleksowej oceny obecnej sytuacji i zmian, jakie zaszły w latach 1991-2009 w zakresie różnych elementów wzrostu gospodarczego w niemieckich krajach związkowych. W tym celu zaproponowano pięciomodułowy schemat syntetyzujący najważniejsze czynniki i umożliwiający opracowanie cząstkowych, a następnie syntetycznego wskaźnika oceniającego potencjał wzrostu w poszczególnych regionach. Wyróżniono: 1) konkurencyjność, czyli ujęcie podażowe, nawiązujące do makroekonomicznej funkcji produkcji, 2) podział branżowy dotyczący udziału sektorów we wzroście gospodarczym, 3) koniunkturę, czyli ujęcie popytowe odwołujące się do kardynalnego równanie makroekonomii, 4) kondycję gospodarczą wyznaczoną kształtowaniem się głównych wskaźników makroekonomicznych oraz 5) klimat gospodarczy obejmujący pozostałe potencjalne determinanty wzrostu gospodarczego. Schemat stanowiący eklektyczne podejście do czynników wzrostu jest próbą wypełnienia luki między wysoce zmatematyzowanym modelowym i abstrakcyjnym ujęciem kwestii wzrostu, jaki przeważa w literaturze akademickiej, a podejściem praktycznym obecnym w prasie biznesowej, czy bieżących analizach politycznych. Otrzymane wyniki wskazują, że najwyższy potencjał wzrostu gospodarczego osiągnęły Bawaria, Badenia Wirtembergia i Nadrenia Północna Westfalia; najsłabszy - Berlin, Brema, Saksonia Anhalt i Meklemburgia Pomorze Przednie. Rezultaty te potwierdzają po części wcześniejsze wnioski innych badań o wciąż utrzymujących się dysproporcjach Wschód -Zachód, ale wskazują też na postęp, jaki wschodnie Landy osiągnęły od momentu Zjednoczenia.