Casey Introduces Bill to Green Urban Areas

WASHINGTON, DC – U.S. Senator Bob Casey (D-PA) introduced the Green Communities Act, S.3055, which would help communities create green strategies to improve quality of life, attract new business and improve the general environment in urban areas.

“Research shows that urban greening not only improves the quality of life for residents, but also attracts new business, generates economic growth and creates jobs,” said Senator Casey. “It is more important now than ever to focus on new ideas that will restore the health of our economy and will get people back to work. That’s why I introduced the Green Communities Act to assist cities in planning, designing and implementing green infrastructure strategies.”

The Green Communities Act creates a new program through the Department of Commerce’s Economic Development Administration. This program will encourage public-private partnership by contracting with five nationally recognized non-profit organizations that will provide technical assistance to 80 municipalities across the United States. After the communities have completed the technical assistance portion, they will be eligible for additional grant funding to help implement their green planning.

The Green Communities Act is endorsed by groups including: America In Bloom, Alliance for Community Trees, American Nursery & Landscape Association , National Association of Clean Water Agencies, OFA – An Association of Floriculture Professionals, Pennsylvania Association of Boroughs, Penn Future, Pennsylvania Horticultural Society, Pennsylvania Landscape & Nursery Association, Perennial Plant Association, Professional Landcare Network, Project EverGreen, Society of American Florists, Tree Care Industry Association and Turf and Ornamental Communicators Association.

The legislation has also been introduced in the House of Representatives by Congresswoman Allyson Schwartz (D-PA).

There's a market for anything!

Florida's special python hunting season has begun...which proves the point, economically speaking, that a market can be established for just about anything.

Click here for the full story.

If you want a good laugh from a snake story well told, click on his link at the bottom (r.e. his irrational view of snakes).

The Effect of Immigration on Productivity

Immigration during the 1990s and the 2000s significantly increased the presence of foreign-born workers in the United States, but the increase was very unequal across states. In The Effect of Immigration on Productivity: Evidence from US States (NBER Working Paper No. 15507), NBER Research Associate Giovanni Peri analyzes state-by-state data to determine the impact of immigration on a variety of labor market outcomes, including employment, average hours worked, and average skill intensity, and on productivity and income per worker.

Peri reports a number of distinct findings. First, immigrants do not crowd-out employment of (or hours worked by) natives; they add to total employment and reduce the share of highly educated workers, because of their larger share of islow-skilled relative to native workers. Second, immigrants increase total factor productivity. These productivity gains may arise because of the more efficient allocation of skills to tasks, as immigrants are allocated to manual-intensive jobs, promoting competition and pushing natives to perform communication-intensive tasks more efficiently. Indeed, a measure of task-specialization of native workers induced by immigrants explains half to two thirds of the positive effect on productivity.

Third, Peri finds that inflows of immigrants decrease capital intensity and the skill-bias of production technologies. The decrease in capital intensity comes from an increase in total factor productivity; the capital-to-labor ratio remains unchanged because investment rises coincident with the inflow of immigrants. The reduction in the skill-intensity of production occurs as immigrants influence the choice of production techniques toward those that more efficiently use less educated workers and are less capital intensive.

Finally, Peri finds that for less educated natives, higher immigration has very little effect on wages, while for highly educated natives, the wage effect of higher immigration is positive. In summary, he finds that a one percent increase in employment in a US state, attributable only to immigration, is associated with a 0.4 to 0.5 percent increase in income per worker in that state.

A central challenge in establishing a causal link between immigration and economic outcomes is the fact that immigrants may be disproportionately attracted to states with strong economic performance. Peri recognizes this problem, and uses information on state characteristics, such as the location of a state relative to the Mexican border, the number of ports of entry, as well as the existence of communities of immigrants there before 1960 to predict immigrant inflows. He then studies how these predicted inflows, rather than actual inflows, are related to labor market outcomes. He argues that the state characteristics that underlie his predictions are not likely to be associated with either labor market outcomes or productivity. He also controls for several other determinants of productivity that may vary with geography such as R and D spending, computer adoption, international competition in the form of exports, and sector composition.

What the Stock Market Decline Means for Financial Security and Retirement Choices

The recent decline in stock market values will have only a muted impact on the retirement of the average early baby boomer, according to NBER Research Associate Alan Gustman and his co-authors Thomas Steinmeier and Nahid Tabatabai. In What the Stock Market Decline Means for the Financial Security and Retirement Choices of the Near-Retirement Population (NBER Working Paper No. 15435), they explain that with only around 15 percent of the wealth of workers aged 53 to 58 in stocks, they aren't likely to see a huge hit to their retirement portfolios, despite the market losing roughly a third of its value from its 2007 peak through the fall of 2009. More than a quarter of the household wealth of this group is instead concentrated in anticipated Social Security payments.

The pension wealth of this group is far more dependent on traditional pensions, called defined benefit plans, than on 401(k)s or defined contribution plans, which often are heavily reliant on stock market performance. The simulations in this study suggest that the declines in the stock market will only cause early boomers to postpone retirement by an average of 1.5 months. The drop in housing prices is also unlikely to greatly affect their retirement plans.

"For most of those approaching retirement age, while losing several percentage points of this total is certainly a significant average loss -- and is of greater significance for those who are more exposed to the stock market and will experience even larger losses -- these losses will not be life-changing," the authors conclude.

Early boomers might seem to be especially vulnerable to the twin declines in stock and housing markets, since they have little time to recover before reaching retirement age. A 2006 survey of nearly 2,500 households in which at least one member was 53 to 58, conducted as part of the Health and Retirement Study, found that these households had an average of $766,945 in total wealth. But Social Security was their single largest asset, representing 26 percent of total wealth on average. Pensions were the second largest source of wealth: 23 percent on average. Home equity averaged 22 percent. Stocks in defined contribution plans and held directly accounted for only $116,535, or about 15 percent of the total.

To estimate the effect of stock market declines on retirement, this study looks at the last stock-market plunge: the bursting of the dot com bubble in the early 2000s. It concludes that stock-market plunges have a modest effect on older workers and change the average age of retirement by only a few months. In addition, these modest delays in retirement by some workers trying to make up for stock losses may be swamped by the number of early retirements caused by a lack of good jobs. Even if the stock market decline, taken alone, modestly decreases the number of retirements, the recession that started in 2007 may substantially increase retirement due to poor job prospects, the authors write. Thus, the net effect of a deep recession and a falling stock market may be an overall increase in retirements.

On the housing front, the fallout from the big decline in home prices may also be muted for early boomers. Nearly half of early boomer households had no mortgage. Almost all of the rest had positive equity. Mortgages represented 39 percent of their home values on average, leaving only a tiny sliver of early boomers 1.7 percent with negative home equity in 2006. If housing prices were to fall 20 percent, only 6.4 percent of the households in this age group would be "under water," according to the study. Typically, it will be many years before these boomers sell their homes to capture the equity in them.

The study points out that some early boomers may be affected by the combination of stock and housing declines. Those who lose a job may have to retire early or take another job that will likely pay much less. This diversity of winners and losers poses a major policy challenge for those wanting to extend government help to hard-hit early boomers.

Household Spending Response to the 2008 Tax Rebate

Between April and December of 2008, about 120 million individuals in the United States received one-time stimulus payments totaling $96 billion. Those payments began phasing out at incomes above $75,000 a year, in part because it was argued that lower-income households were more likely to spend their rebates, so policies aimed at those households would be more likely to have stimulative effects.

In Household Response to the 2008 Tax Rebate: Survey Evidence and Aggregate Implications (NBER Working Paper No. 15421), co-authors Claudia Sahm, Matthew Shapiro, and Joel Slemrod find that the proportion that people say they spent was up slightly as compared to previous stimulus-induced spending. They estimate that the $96 billion spent on stimulus generated roughly one third that amount, or $32 billion, in extra consumer spending (as compared to 21% spending of previous stimuli).

This study uses data from The Reuters/University of Michigan Survey of Consumers, a nationally representative survey based on 500 telephone interviews a month. The authors compare the results of their analysis to aggregate data on saving, spending, and debt, and to the results from other surveys. They conclude that their results are in accord with these data, and that "absent the rebate, the sharp decline in spending that is evident in aggregate data beginning in the third quarter of 2008 would have started in the second quarter, prior to the financial crisis of the fall."

Although the authors find that the stimulus program boosted consumer spending, they report that more than three-quarters of the overall survey respondents said that they would save the stimulus payments or use them to pay down debt. Of those under age 30, only 11 percent said they would mostly spend the payments. Of those over age 65, 26 percent said they would mostly spend the payments. These results are similar to those observed for the 2001 tax rebates.

People with incomes over $75,000 -- roughly the top third of the income distribution -- had "mostly-spend" rates about 7 percent higher than the average mostly-spend rate of lower income groups. For those with stock holdings in excess of $250,000, the mostly-spend rate was almost 40 percent; for those with stock valued between $100,000 and $250,000, that rate was 25 percent; for those with stock holdings between $50,000 and $100,000, the mostly-spend rate was 14 percent; and for those with stock holdings below that level, the mostly-spend rate was roughly 20 percent. These results do not support the conventional wisdom that younger, lower-income households are more likely to spend a one-time tax rebate. They are consistent with the possibility that moderate-stock-wealth households are more inclined to save because, unlike high-stock-wealth households, they have not yet met their savings goals.

Olympic-sized Update

I had a few folks comment that my last post was perhaps the most negative that they had seen on Making Cents (given my tendency to try to find the silver lining in most cloudy situations), but remember, I was quoting Bill Kirk who is the CEO of Weather Trends International. I did so because Bill and the folks at WTI have an amazingly accurate track record of forecasting retail sales based on their weather models.

So after the February retail report actually showed same-store retail sales actually INCREASED by 3.7%, I emailed Bill the following:

Bill:
After your persuasive post on the downward expectations on February SSS sales due to snowmageddon conditions, I’ve been checking the SSS reports released today (from ICSC and others) which seem to indicate a 4% increase for the month, which is actually higher than the 2-3% Wall Street expectations. Is this correct? If so, given your excellent track record, is this just one you missed this time?
Thanks for your input,
Charlie

As usual, Bill is always prompt in returning comments on WTI forecasts and he emailed back with the following reply:

Charlie,
Good morning. Retailers for the most part were all well above expectations but many did comment that the record snow cost them 1% to 2% in lost sales. Bottom line, they overcame the 9 major hurdles but they were up against the easiest February comp ever last year which was -4.3% so the +3.7% gain captured most but not all of last year’s huge losses. The expectations for March have been set very low at +2.5% by Wall Street but with the first major Spring surge of warm weather late month around Easter, retailers are poised for a blow out month with exceptional sales gains well above expectations. Why? Because they’ve had two back-to-back really bad March sales in 2008 = -2.3% and last year -5.1% due in large part to cold/snowy weather around Easter the past two years. Net-net we missed this one but Wall Street was surprised by the prior 2 strong months so we’re still up on the street!
Bill

I agree. I still hold a great deal of respect and will continue to follow the weather-based retail modeling by WTI (and others) because they represent one more layer of information to help us all in making more informed managerial decisions. Just goes to show that its hard for anyone who's brave enough to do some forecasting to get it right 100% of the time!

That being said, I do agree with Bill that expectations for March are OPTIMISTIC given the level of "pent-up demand" that is generally being touted in the marketplace. Again, last spring was pretty good given the circumstances and with the industry going into this spring with consumer confidence a lot higher than last year; the Conference Board's leading economic indicator index having increased for the 10th straight month; and the latest job market report mostly positive, I feel we are positioned about as well as we could be going into the spring season.

All that is left to do now is to put our best differentiated foot forward and make sure that we not only exceed consumer expectations, but delight them in the process!

Nine Olympic-sized Hurdles For February Retail SSS

From Bill Kirk of Weather Trends International:

There is a growing avalanche of bad news for overall February 2010 retail industry same-store-sales. Results are announced March 4th – here are 10 reasons why they will likely come in much lower than the +2% to +3% expectations on Wall Street:

1. Snowmageddon! February national snowfall will be off the chart and likely to crush all records for the snowiest February in 115 years. It’s tough to convince consumers to make Spring purchases when snow is all we see. THIS IS A BIG NEGATIVE!

2. The most highly correlated external factor to overall retail industry same-store-sales (SSS) is SNOW with an 84% correlation toward LESS being more favorable for higher SSS. Over the past 30 years, a snowier February results in lower than expected SSS for 82% of cases. THIS IS A BIG NEGATIVE!

3. A cold/wet/snowy February average SSS are +1.3% over the past 30 year’s vs a warm/dry/little snow February which brings much higher SSS of +6.7%. THIS IS A BIG NEGATIVE!

4. There were 21 days this February with significantly more snow than last year and the most snow before Valentine’s and President’s Day in decades. Nearly 70% of the country was covered in snow (49 of 50 states) prior to Valentine’s Day – the most on record. THIS IS A BIG NEGATIVE!

5. The Consumer Confidence Index is the 2nd most correlated external factor to retail industry SSS at 73%. While February consumer confidence came in at 46, much lower than the 55 predicted, it is down from the 56 in January. 90 is considered a good economy. THIS IS A BIG NEGATIVE!

6. The next most correlated factor is temperature (46%) with warmer being better. February 2010 is on pace to be the coldest since the 1970s (30+ years) with a 5.2F drop from last year. Every 1F colder can cost retailers up to 0.7% in lost sales. THIS IS A BIG NEGATIVE!

7. A stronger than expected January (we had that in 2010 with the +3% gain) is followed by a weaker than expected February in 63% of cases over the past 30 years. THIS IS A NEGATIVE!

8. Unemployment is at +9.7% this February vs +8.1% a year ago. THIS IS A NEGATIVE!

9. Gasoline prices are up +39% vs a year ago at $2.66 a gallon vs $1.91 gallon. THIS IS A NEGATIVE.

10. THE ONE BIG POSITIVE? Very easy comparisons to last year February SSS results which were the worst in 30 years at -4.3% according to data from ICSC. If it wasn’t for this easy comp, February 2010 would be a complete disaster; even with the easy comp results are likely to be much lower than expected!

Stay tuned for the March 4 report to see how WTI's forecast comes out.