Unbalanced growth

Abstract.  We study a model designed to understand the concept of unbalanced growth. We define leading sectors to be those that raise the profits from industrialization for other sectors the most. We identify the leading sectors and show that subsidizing them in sequence will raise welfare if the future is not discounted too strongly.     

The service sector and economic growth: some cross-section evidence

It has often been claimed that a relative expansion of the service sector has a deleterious effect on economic growth. This paper uses cross-section country-level data from three decades –1960s, 1970s and 1980s – to see whether in fact this negative relation is reflected in the data. It is found that the effect is negative or positive depending on how the role of the service sector is measured, but there is a strong case that effect is in fact usually negative.     

Subscriber return, underpricing, and long-term performance of U.K. privatization initial public offers

This study distinguishes between issuer underpricing and subscriber returns, and estimates their magnitudes for U.K. privatization initial public offers (PIPOs). It proposes and tests empirical models which incorporate theoretical, institutional, and other factors which interact to explain subscriber returns and issuer underpricing. The estimates reveal that, on average, issuer underpricing, which is measured relative to the total equity market value on the first day of trading, is 23.62%, whereas the average raw return available to subscribers is up to 41%. Regression analysis shows that underwriters' commission, market volatility, regulatory situation of the company, proportion of share clawback, and demand for shares taken together explain up to 70% of the variation in issuer underpricing and 64% of subscribers' returns. The evaluation of the long-run performance of PIPOs to assess the extent to which initial gains to subscribers persist for longer periods concludes that U.K. PIPOs, on average, provide long-run holding gains to investors, unlike their private sector counterparts.     

The new science of sales force productivity

For years, sales managers at many companies have relied on top performers and sheer numbers of sales reps to stay competitive. But while they may have squeaked by on this wing-and-a-prayer technique, their sales teams haven't thrived the way they once did. Today's most successful sales leaders are taking a more scientific approach. Savvy managers are reshaping their tactics in response to changing markets. They are reaching out to new customers in innovative ways. And they are increasing productivity by helping the reps they already have make the most of their skills and resources. Leaders who take a scientific approach to sales force effectiveness have learned to use four levers to boost their reps' productivity in a predictable and manageable way. First, they systematically target their firms' offerings, matching the right products with the right customers. Second, they optimize the automation, tools, and procedures at their disposal, providing reps with the support they need to boost sales.Third, they analyze and manage their reps' performance, measuring both internal processes and results to determine where their teams' strengths and weaknesses are. Fourth, they pay close attention to sales force deployment--how well sales, support, marketing, and delivery resources are matched to customers. These four levers can help sales leaders increase productivity across the board, the authors say, though they have the greatest impact on lower-ranked performers. The overall effect of increasing the average sales per employee can be exponential; it means a company won't have to rely on just a few talented individuals to stay competitive. This is especially important because finding and keeping star salespeople is more difficult than ever. What's more, managers who optimize the sales forces they already have can see returns they never thought possible.     

Analysts' Forecasts of German Firms' Earnings: a Comparative Analysis

This paper examines analysts' forecasts of the annual earnings per share of German firms over the period of February 1987 to December 1995. The German case is particularly interesting as the accounting and institutional structures vary from those in more thoroughly researched markets such as the U.S. or U.K. The paper therefore considers the features of the German forecasting environment which distinguish it from the Anglo-American model, and whether these might be reflected in forecasting performance. The results for Germany show that the accuracy of analysts' forecasts improves as the forecast horizon shortens, are less accurate than a naive prediction model over longer horizons, and contain a positive bias. When the results for Germany are contrasted with the results for the U.K., as reported in a recent paper, they are found to be a little less accurate but the positive bias is greater in U.K. forecasts. Taken overall the forecasting process in Germany appears to be less efficient than in the U.K., but this may be due to the distinct features of the German forecasting environment.     

THE IMPACT OF LABOR MARKET REGULATION ON EMPLOYMENT IN LOW‐INCOME COUNTRIES: A META‐ANALYSIS

Controversy over labor market policy often centers on achieving a balance between preventing worker exploitation, and avoiding loss of productivity or employment through excessive regulation. Although the literature documenting the impact of labor market regulation on employment is extensive, there is a dearth of evidence on the impact of such policies in low‐income countries (LICs). Since it is easier for workers, especially women, to slip into the informal sector in LICs, regulations are likely to have stronger impacts on formal employment in these countries (but lower impacts on unemployment). We systematically reviewed available research from countries that are, or were until recently, LICs. Most studies document that more stringent labor regulations are associated with lower formal sector employment and higher informal sector employment. We also conducted a metaregression analysis of the impact of minimum wages on formal and informal employment. After controlling for publication bias, higher minimum wages are associated with lower formal employment and a higher share of informal workers.