Development Starts With Historical Endowments: Industrial Policy and Leadership Are Catalysts

2021 ◽  
pp. 089124242110248
Author(s):  
Edward (Ned) Hill
Keyword(s):  
Industrial Policy ◽  
Research Universities ◽  
High Tech ◽  
Metropolitan Statistical Area ◽  
Regional Economies ◽  
Development Programs ◽  
Metropolitan Statistical Areas ◽  
Self Interest ◽  
Technology Resources ◽  
Statistical Area

Ben Armstrong compares the implementation of regional economic development programs in the Pittsburgh and Cleveland metropolitan statistical areas during the 1980s. He argues that their regional economies and research institutions were then similar. He contends that the transformational policy difference occurred when Pennsylvania’s governor mandated that the presidents of Pittsburgh’s research universities be programmatic leaders while Ohio’s governor did not do the same. Armstrong concludes that Pittsburgh’s Metropolitan Statistical Area became a center of high-tech innovation as a result, while Cleveland’s did not. This author contends that disparities in regional technology resources, as well as institutional self-interest and leadership, were the critical differences. Cleveland’s institutions had to give priority to fixing their business problems. Armstrong and the author agree that economic endowments and industrial policy played roles in both regions’ economic outcomes; where they disagree is on the weights given to each.

Hot and cold seasons in Texas housing markets

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mustafa Hattapoglu ◽  
Indrit Hoxha
Keyword(s):  
Design Methodology ◽  
National Level ◽  
Housing Markets ◽  
Metropolitan Statistical Area ◽  
Macroeconomic Factors ◽  
Content Type ◽  
Metropolitan Statistical Areas ◽  
Two Measures ◽  
Mortgage Rates ◽  
Statistical Area

Purpose This paper aims to use statistical analyses to understand the trends on housing liquidity and pricing by accounting for macroeconomic factors that vary at national level and at metropolitan statistical area level for all metropolitan statistical areas in Texas. In addition, the authors test for seasonality in all the metropolitan statistical areas in Texas. Design/methodology/approach Using publicly available data from Zillow a listing website, the authors conduct an analysis of all housing markets at metropolitan statistical area level in Texas to understand the factors that drive the liquidity and pricing. The authors use two measures for liquidity, namely, time to sell the house and sales to list ratio. The authors also try to understand the decision to lower the price of the listed houses. In addition, the authors conduct a test for seasonality within the year in these housing markets. Findings The analyses conclude that there is a significant impact of listing prices, unemployment rates, 30-year mortgage rates, consumer sentiment and oil price changes on the liquidity of the housing markets and decisions of sellers to adjust the prices down. In addition, the authors provide evidence of the existence of seasonality in most metropolitan statistical areas in Texas both for pricing and volume of transactions. Originality/value This is the first study to look at housing liquidity and pricing trends for about 25 markets in Texas. In addition, the authors provide evidence of the importance of oil prices for the housing markets in Texas metropolitan statistical areas.

scholarly journals US Metropolitan Area Resilience: Insights from dynamic spatial panel estimation

2017 ◽  
Vol 50 (1) ◽  
pp. 111-132 ◽  
Author(s):  
Justin Doran ◽  
Bernard Fingleton
Keyword(s):  
Metropolitan Area ◽  
Industrial Structure ◽  
State Of The Art ◽  
Metropolitan Statistical Area ◽  
Panel Estimation ◽  
Metropolitan Statistical Areas ◽  
Spatial Panel ◽  
Panel Model ◽  
Spatial Panel Model ◽  
Statistical Area

In this paper, we show that the economic crisis commencing in 2007 had different impacts across US Metropolitan Statistical Areas, and seek to understand why differences occurred. The hypothesis of interest is that differences in industrial structure are a cause of variations in response to the crisis. Our approach uses a state-of-the art dynamic spatial panel model to obtain counterfactual predictions of Metropolitan Statistical Area employment levels from 2008 to 2014. The counterfactual employment series are compared with actual employment paths in order to obtain Metropolitan Statistical Area-specific measures of crisis impact, which then are analysed with a view to testing the hypothesis that resilience to the crisis was dependent on Metropolitan Statistical Area industrial structure.

scholarly journals Enterprise As an Object of Industrial Policy

2017 ◽  
Vol 6 (1) ◽  
pp. 39-44
Author(s):  
Девяткин ◽  
O. Devyatkin ◽  
Игнатова ◽  
L. Ignatova
Keyword(s):  
Industrial Policy ◽  
The State ◽  
High Tech

The content of the state industrial policy is considered, the basic objectives and principles of perfection of the mechanism of its implementation are formulated. The attention is paid to the need of developing high-tech industries.

Directions of improving industrial policy in Russia

2021 ◽  
pp. 82-88
Author(s):  
Keyword(s):  
Industrial Policy ◽  
Global Economy ◽  
Manufacturing Industry ◽  
Development Program ◽  
Domestic Market ◽  
Government Support ◽  
High Tech ◽  
Production Structure ◽  
Production Chain ◽  
Intersectoral Cooperation

The correspondence of the current concept of industrial policy of Russia and the tools for its implementation to the solution of the strategic task — the full provision of the needs of the state and the population with industrial goods in the context of the recession of the world economy is considered. It is shown, that government support for the manufacturing industry is not aimed at creating conditions for the accelerated development of the high-tech sector, and the inconsistency of its production structure with the structure of the domestic market for industrial goods in Russia limits the economic effectiveness of domestic production. Prospective directions of government support for the development of the manufacturing industry are substantiated. Keywords: global economy, production chain, management company, government support, intersectoral cooperation, domestic market, manufactured goods, development program, tools, high-tech segment. [email protected]

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