Art Laffer’s Four Prosperity Killers

Art Laffer’s Four Prosperity Killers: "Right now is as good a time as any to revisit my old friend Art Laffer’s four prosperity killers. You can put a check mark next to each one.

1. Rising tax rates
2. Inflationary money
3. Trade protectionism
4. Government control/re-regulation

And while we’re on the subject, make sure to check out Art's terrific op-ed in today’s Wall Street Journal.

He argues that while Fed policy was undoubtedly important, it was ultimately tariffs, rising taxes, and currency devaluation which ruined the 1930s. According to Art, we face the same dangers today.

He’s dead right.

"

Real Lesson from Great Depression: Tax Damage

Real Lesson from Great Depression: Tax Damage: "

Arthur Laffer in today's Wall Street Journal ('Taxes, Depression, and Our Current Troubles') writes:

In 1930-31, during the Hoover administration and in the midst of an economic collapse, there was a very slight increase in tax rates on personal income at both the lowest and highest brackets. The corporate tax rate was also slightly increased to 12% from 11%. But beginning in 1932 the lowest personal income tax rate was raised to 4% from less than one-half of 1% while the highest rate was raised to 63% from 25% (see charts above). (That's not a misprint!) The corporate rate was raised to 13.75% from 12%. All sorts of Federal excise taxes too numerous to list were raised as well. The highest inheritance tax rate was also raised in 1932 to 45% from 20% and the gift tax was reinstituted with the highest rate set at 33.5%.

But the tax hikes didn't stop there. In 1934, during the Roosevelt administration, the highest estate tax rate was raised to 60% from 45% and raised again to 70% in 1935. The highest gift tax rate was raised to 45% in 1934 from 33.5% in 1933 and raised again to 52.5% in 1935. The highest corporate tax rate was raised to 15% in 1936 with a surtax on undistributed profits up to 27%. In 1936 the highest personal income tax rate was raised yet again to 79% from 63%—a stifling 216% increase in four years. Finally, in 1937 a 1% employer and a 1% employee tax was placed on all wages up to $3,000.

Because of the number of states and their diversity I'm going to aggregate all state and local taxes and express them as a percentage of GDP. This measure of state tax policy truly understates the state and local tax contribution to the tragedy we call the Great Depression, but I'm sure the reader will get the picture. In 1929, state and local taxes were 7.2% of GDP and then rose to 8.5%, 9.7% and 12.3% for the years 1930, '31 and '32 respectively.

The damage caused by high taxation during the Great Depression is the real lesson we should learn. A government simply cannot tax a country into prosperity. If there were one warning I'd give to all who will listen, it is that U.S. federal and state tax policies are on an economic crash trajectory today just as they were in the 1930s. Net legislated state-tax increases as a percentage of previous year tax receipts are at 3.1%, their highest level since 1991; the Bush tax cuts are set to expire in 2011; and additional taxes to pay for health-care and the proposed cap-and-trade scheme are on the horizon.

"

Philly Fed Index

Philadelphia Fed. (United States) {US} OBSERVATION PERIOD: SEP (Monthly)

ACTUAL : 14.1

PRIOR : 4.2

REVISED : - -

SURVEY : 8.0 (Mean: 8.3, High: 14.4, Low: 2.5)

Philly Fed Index is a measure of business growth. The index is constructed from a survey of participants who voluntarily answer questions regarding the direction of change in their overall business activities. The survey is a measure of regional manufacturing growth. When the index is above 0 it indicates factory-sector growth, and when below 0 indicates contraction.

This index is published by the Philadelphia Federal Reserve Bank on the third Thursday of the month at 10 am EST. It is considered to be a good gauge of general business conditions.

Actual number came in at 14.1, with 8.0 being expected, and 4.2 the prior month. This is an indication of increasing business growth.

TED Spread Has Fallen 450 Bps in Last Year, Now At The Lowest Level in 5 Years, Since June 8, 2004

TED Spread Has Fallen 450 Bps in Last Year, Now At The Lowest Level in 5 Years, Since June 8, 2004: "The TED spread is the difference between the risk-free three-month T-bill interest rate and three-month LIBOR (includes a credit risk premium), and is considered to be a good indicator of the overall amount of perceived credit risk in the economy. A year ago on September 15, 2009 the TED Spread jumped by 65.5 basis points (from 134.855 bps to 200.3588 bps) as Lehman Brothers filed for bankruptcy and fears about credit risk soared. Two days later on September 17 as fears about credit and financial risk intensified, the TED Spread jumped by another 82.6 basis points (bps) to more than 300 bps, setting a new record (back to at least 1990) for the largest one-day increase in the TED spread (that record still stands), and setting a new record for the highest TED Spread to date.

At the height of the financial crisis about a month later, the TED Spread hit 456.485 basis points on October 13, 2008, an all-time record. As the credit and financial markets have gradually healed, the TED Spread has fallen by more than 450 bps to the current level of about 15.75 bps, the lowest level in more than 5 years, since June 8, 2004 (see chart above). One more sign that the recession has ended.

"

Steve: This is a good indication of credit freeing up in financial markets.

It's Not Bloomberg, But it's Free!

Yesterday I was checking out Google Docs. I have never spent much time with it, because it's no Excel, but it does have some cool features. One feature in specific caught my eye. In conjunction with Google Finance, Google Docs can become a useful market tool. Now it's no Bloomberg, and doesn't have anywhere near the functionality that Bloomberg's API add-on for Excel has, but it's a start. Here is more detailed instructions on how it works.

The GoogleFinance function uses the syntax: =GoogleFinance("Symbol","Attribute"); where "Symbol" represents the ticker of the stock or mutual fund you're looking for, and "Attribute" represents the type of market data desired (price, volume, change, etc). Also, the function allows you to get historical data on stock price, etc. So, this tool can be leveraged to create automated watch lists and models using Google Docs. Currently the amount of data that can be pulled from Google Finance on one sheet is limited, but for being free, one can't complain too much. Bloomberg limits you to 500,000 pulls per day, and I've reached that limit a few times. But, for those who want a free alternative, this works for basic data. Hopefully, Google will add the ability to pull data from financial statements (Revenue, NI, etc.).

To find the current market price of Google (GOOG), use the syntax: =GoogleFinance("GOOG","Price"); and the current price will be updated continuously.

Current market attributes available:

• price: market price of the stock - delayed by up to 20 minutes.
• priceopen: the opening price of the stock for the current day.
• high: the highest price the stock traded for the current day.
• low: the lowest price the stock traded for the current day.
• volume: number of shares traded of this stock for the current day.
• marketcap: the market cap of the stock.
• tradetime: the last time the stock traded.
• datadelay: the delay in the data presented for this stock using the googleFinance() function.
• volumeavg: the average volume for this stock.
• pe: the Price-to-Earnings ratio for this stock.
• eps: the earnings-per-share for this stock.
• high52: the 52-week high for this stock.
• low52: the 52-week low for this stock.
• change: the change in the price of this stock since yesterday's market close.
• beta: the beta value of this stock.
• changepct: the percentage change in the price of this stock since yesterday's close.
• closeyest: yesterday's closing price of this stock.
• shares: the number of shares outstanding of this stock.
• currency: the currency in which this stock is traded.

Current attributes for mutual funds:

• closeYest: the NAV of a mutual fund.
• date: date at which NAV (net asset value) was reported.
• returnytd: year-to-date return total.
• netassets: The day-end net assets of the mutual fund. Net-asset figures are useful in gauging a fund's size, agility, and popularity. They help determine whether a small company fund, for example, can remain in its investment-objective category if its asset base reaches an ungainly size.
• change: change in NAV value between the most recent reported NAV, and the NAV prior to that.
• changepct: the % change in the NAV.
• yieldpct: Also known as the distribution yield, Morningstar computes this End Yield figure by summing the trailing 12-month's income distributions and dividing the sum by the last month's ending NAV, plus capital gains distributed over the same time period. Income refers only to interest payments from fixed-income securities and dividend payments from common stocks.
• returnday: one-day total return.
• return1: one-week total return.
• return4: four-week total return.
• return13: thirteen-week total return.
• return52: 52 week total return.
• return156: 156 week total return.
• return 260: 260 week total return.
• incomedividend: the amount of the most recent cash distribution for the fund.
• incomedividenddate: the date the above occurred.
• capitalgain: the amount of the most recent capital gain distribution from the fund.
• capitalgaindate: the date of the above.
• morningstarrating: the Morningstar "star" rating.
• expenseratio: The percentage of fund assets used to pay for operating expenses and management fees, including 12b-1 fees, administrative fees, and all other asset-based costs incurred by the fund, except brokerage costs. Fund expenses are reflected in the fund's NAV. Sales charges are not included in the expense ratio.

I created the watch list below in about 10 minutes. During trading hours it updates continuously. Click the image to enlarge.

Here is the link to the worksheet in Google Docs.
Another example can be found here.

S&P 500 Sector Stats

Below is a table of returns and P/E for the S&P 500 separated by sectors. Data is as of today.

Click to enlarge.

Market Stats