Inflation Peaks/Real-gdp Peaks/Interest Rates Peak

[Finster]

Re: Inflation Peaks/Real-gdp Peaks/Interest Rates Peak

i had missed post151. i regret that i can't respond because my knowledge of minsky is too limited. i don't know his work well enough.

later:
[iirc, the intermediate form of debt, where cash flows will pay the debt, is based on the notion of self-liquidatation]

I am not a Minsky expert either, so was mostly working from your characterization. Although there was nothing concrete there to pin it on, it looked like the whole context, except perhaps for the third level, was under the assumption of "self-liquidating" debt. Although it's not conclusive since consumer borrowing could occur under the first two. In addition, the term "self-liquidating" itself is a little ambiguous.

Either way, the concept of differentiating between debt undertaken for productive purposes and that taken for the purpose of consumption or speculation is important. The debt incurred to build the factory or develop technology might be termed "self-liquidating" not because of mere cash flow, but because real value is created with which to service the debt. Interest can be paid from real profit. Perhaps it sounds like an old-fashioned concept in these days of the "FIRE economy", but it is only in this circumstance where we can escape the "zero-sum-game" constraint and both the lender and borrower can win. Hence the notion that the return-risk proposition can be much more favorable.

[flow5]

Re: Inflation Peaks/Real-gdp Peaks/Interest Rates Peak


The FED's balance sheet is published once a year:

http://www.federalreserve.gov/boardd...06/default.htm

Income & Expense statements for each of the twelve Federal
Reserve Banks are printed on their annual reports on each banks website.

[Finster]

Re: Inflation Peaks/Real-gdp Peaks/Interest Rates Peak

The FED's balance sheet is published once a year:

http://www.federalreserve.gov/boardd...06/default.htm

Income & Expense statements for each of the twelve Federal
Reserve Banks are printed on their annual reports on each banks website.

Thanks, Flow. See anything of broad significance there?

[flow5]

Re: Inflation Peaks/Real-gdp Peaks/Interest Rates Peak

xxxxxxxxxxxxxxxxxxxxx

[flow5]

Re: Inflation Peaks/Real-gdp Peaks/Interest Rates Peak

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[flow5]

Re: Inflation Peaks/Real-gdp Peaks/Interest Rates Peak

Outline

LABELING MODELS
K-MEANS MODEL
FINITE MIXTURE MODEL
MEAN-SWITCHING MODEL
AUTOREGRESSIVE MEAN-SWITCHING MODEL
AUTOREGRESSION COEFFICIENT-SWITCHING MODEL
__________________________________________________ ___________________________

Thursday, 24-April-2003:

In our consideration of economic and financial time series several models have been discussed. In these notes some of these will be listed and algorithms for estimation will be proposed. The notes will progress from simple to more complicated models. The simplest model for the error variance is used; ARCH and GARCH models can be combined with the listed models, but we do not do this now.

Denote the series to be analyzed by { yt , t = 1,2, . . . , n }. In most of what follows, this will be a time series. The the index t denotes the instant of time at which the observation was made, or the period of time during which it was made. The series may be an observed series or a series derived from an observed series.
__________________________________________________ ___________________________

Examples.
(i) Let {xt} be an observed price series of a stock, and let
yt = ln xt - ln xt-1.
Then yt is the continuous rate of return ( ROR ) of {xt}. (cont.ROR)
(ii) Let GNPt be, say, quarterly GNP. (GNP) Then
yt = Δ ln GNPt = ln GNPt - lnGNPt-1 ,
may be considered as the velocity of the economy. Similarly,
Δ2 ln GNPt = Δ(Δ ln GNPt)
= ( ln GNPt - lnGNPt-1 ) - ( ln GNPt-1 - lnGNPt-2)
= ln GNPt - 2 lnGNPt-1 + ln GNPt-2
may be considered as the acceleration of the economy. Sometimes such differences will be seasonal, such as ln GNPt - ln GNPt-4 , or mixed seasonal and non-seasonal such as
( ln GNPt - lnGNPt-4 ) - ( ln GNPt-1 - ln GNPt-5)
= ( ln GNPt - lnGNPt-1 ) - ( ln GNPt-4 - ln GNPt-5) . __________________________________________________ ___________________________


In other cases the dataset may not be a time series, but a set of observations resulting from a random sample. In this situation, the index t relates to the instance of observation, or the case.

Multivariate data

The random variable yt may be a vector, but it suffices to consider it as a scalar to develop most of the ideas. When it is a vector, we denote its dimension by p , although that is an overworked symbol.


LABELING MODELS

Labels
Many datasets consist of cases from several, say K, groups. Then there are several variables which are measurements, plus an additional variable which is a "label," a categorical variable taking values 1, 2, . . . , K, telling which group each case is from. This variable can be replaced by K indicator variables. So, suppose that at instance t there is not only yt but also a label zt which indicates the label, or state, 1, 2, . . ., or K. We write zt as
ztT = ( z1t z2t . . . zKt) .
(The notation vT denotes the transpose of the vector v.) We write the whole observation set as
{xt , t = 1,2, . . . , n },
where
xtT = ( y tztT ) .
Sometimes it will be more convenient to indicate the states with scalar variables st = 1, 2, . . ., K such that zkt = 1 if st = k and = 0 otherwise, that is,

st = k iff. ztT = (0 0 . . . 0 1 0 . . . 0)

with the 1 in the k-th position.

__________________________________________________ ___________________________
Example. The iris dataset (Anderson 1935,1936, Fisher 1936), often used as an example, consists of four variables, measurements of each of 50 flowers from each of three species of iris. The "labels" are the three species names.
__________________________________________________ ___________________________

Hidden labels
In the situations to be considered here, the label is not given. So suppose that at time t there is not only yt but also an unobserved ("hidden") label zt which indicates the state, 1, 2, . . ., or K. We write zt as
ztT = ( z1t z2t . . . zKt) .

(The notation vT What does the Yield Curve Tell us about GDP

Growth?
∗
Andrew Ang,
†
Monika Piazzesi
‡
and Min Wei
§
October 15, 2003
Abstract
A lot, including a few things you may not expect. Previous studies find that
the term spread forecasts GDP but these regressions are unconstrained and do
not model regressor endogeneity. We build a dynamic model for GDP growth
and yields that completely characterizes expectations of GDP. The model does not
permit arbitrage. Contrary to previous findings, we predict that the short rate has
more predictive power than any term spread. We confirm this finding by forecasting
GDP out-of-sample. The model also recommends the use of lagged GDP and the
longest maturity yield to measure slope. Greater efficiency enables the yield-curve
model to produce superior out-of-sample GDP forecasts than unconstrained OLS
at all horizons.
∗
We thank seminar participants at Columbia University, MIT, Northwestern University, USC, an
NBER EFG meeting, the Stanford-San Francisco Federal Reserve conference on finance and macroeco-
nomics, the workshop on term structure and economic activity at the Federal Reserve Bank of Cleveland
and the IGIER-PIER conference on economic methods in finance and macroeconomics at Bocconi Uni-
versity. We thank Geert Bekaert, Charlie Calomiris, Mike Chernov, John Cochrane, Frank Diebold, Sen
Dong, Bob Hodrick, Urban Jermann, Lutz Kilian, Rick Mishkin, Glenn Rudebusch, Martin Schneider,
Suresh Sundaresan, Mark Watson and Mike Wickens for helpful discussions. Andrew Ang and Monika
Piazzesi both acknowledge funding from the NSF.
†
Columbia Business School and NBER, 3022 Broadway 805 Uris, New York NY 10027; Email:
aa610@columbia.edu; ph: 212 854 9154; WWW: http://www.columbia.edu/∼aa610
‡
University of Chicago and NBER.Graduate School of Business, 1101 East 58th St,
Chicago, IL 60637; Email:
monika.piazzesi@gsb.uchicago.edu; ph:
773 834 3199; WWW:
http://gsbwww.uchicago.edu/fac/monik...zesi/research/
§
Columbia Business School, 3022 Broadway 311 Uris, New York NY 10027; Email:
mw427@columbia.edu; ph: 212 864 8140; WWW: http://www.columbia.edu/∼mw427
1

---

Page 2

1 Introduction
The behavior of the yield curve changes across the business cycle. In recessions, premia
on long-term bonds tend to be high and yields on short bonds tend to be low. Recessions,
therefore, have upward sloping yield curves. Premia on long bonds are countercyclical
because investors do not like to take on risk in bad times. The lower demand for long
bonds during recessions lowers their price and increases their yield. In contrast, yields
on short bonds are procyclical because of monetary policy. The Federal Reserve lowers
short yields in recessions in an effort to stimulate economic activity. For example, for
every 2 percentage point decline in GDP growth, the Fed should lower the nominal yield
by 1 percentage point according to the Taylor (1993) rule.
Inevitably, recessions are followed by expansions. During recessions, upward sloping
yield curves not only indicate bad times today, but better times tomorrow. Guided
from this intuition, many papers predict GDP growth with the slope of the yield curve
in OLS regressions.
1
The higher the slope or term spread, the larger GDP growth is
expected to be in the future. The slope is usually measured as the difference between
the longest yield in the dataset and the shortest maturity yield. Related work by Fama
(1990) and Mishkin (1990a and b) shows that the same measure of slope predicts real
rates. The slope is also successful at predicting recessions with discrete choice models,
where a recession is coded as a one and other times are coded as zeros (see Estrella
and Hardouvelis, 1991; Estrella and Mishkin, 1998). Finally, the term spread is also an
important variable in the construction of Stock and Watson (1989)’s leading business
cycle indicator index. Despite some evidence that parameter instability may weaken the
performance of the yield curve in the future (see comments by Stock and Watson, 2001



BiMetalAUPT


AS BEFORE TARGET M1= TARGET INFLATION +TARGET GDP GROWTH... MAN OH MAN IS THE FED WRONG!!!

POOLE AND HOENIG HAVE MADE IT CLEAR THE FED RANGE IN INFLATION IS 1 TO 2% ... WITH HOUSING PRICES CRASHING WE ARE UNDER 2%... AND THE GDP GROWTH OF 2.5% IN THE MIDPOINT OF NUTURAL...SO 3.5% GROWTH IN M1 EVERY DAY AND 365/7 IS A PROVEN SYSTEM FOR THE BEST GROWTH WITH AS LITTLE INFLATION .. SOLID GROWTH AT NORMAL LEVELS WITH MAX PRODUCTIVITY..

JUST A THOUGHT,
BRUCE

[flow5]

Re: Inflation Peaks/Real-gdp Peaks/Interest Rates Peak

Percent change at seasonally adjusted annual rates --M1--M2
----------------------------------------------------------------------------------------------------------------------------------------------
Thirteen weeks ending August 20, 2007
from thirteen weeks ending:

3 Months from Apr. 2007 TO July 2007 -3.0 3.5
6 Months from Jan. 2007 TO July 2007 -0.5 5.5
12 Months from July 2006 TO July 2007 -0.3 6.1

[flow5]

Re: Inflation Peaks/Real-gdp Peaks/Interest Rates Peak

Although banking mergers and acquisitions have occurred throughout U.S. history, the wholesale decline in the number of banking institutions—or consolidation in the U.S. banking industry—is a more recent phenomenon. As illustrated in Figure 1, the total number of commercial banks in the United States, which had been relatively steady through the 1970s and mid-1980s, has now shrunk to about half of what it was just 20 years ago—from more than 14,000 banks in 1986 to fewer than 8,000 in 2006. The total number of savings institutions (also known as thrifts, savings banks, or savings and loan associations), though not displayed in the figure, has followed an even more dramatic path—shrinking from almost 3,700 thrifts in 1986 to fewer than 1,300 in 2006, or about a third of the 1986 level. - St. Louis Fed 2006 annual report

http://stlouisfed.org/publications/ar/2006/essay2.html

[flow5]

Re: Inflation Peaks/Real-gdp Peaks/Interest Rates Peak

While the total number of independent banking institutions has declined, the number of branches has skyrocketed—from about 66,000 in 1986 to almost 86,000 in 2006. Part of this increase comes from the introduction of unrestricted nationwide interstate branching, which was permitted for the first time in the mid-1990s. Interstate branching has allowed banks to streamline their organizations like never before, opening the door to a new type of bank—one that can operate offices in many different states simultaneously, all as branches of one bank under one bank charter.

ATM availability has increased dramatically since 1986, when there were about 64,000 machines nationwide. By 2004, that number had climbed to upwards of 383,000 units.

Households and small businesses almost exclusively get financial services like checking or other transaction accounts (their primary account) and small-business loans from local financial firms, most often from banks, though sometimes from a thrift or credit union. Regardless of the type of institution, however, the underlying fact still holds: The institution of choice is in the customer’s neighborhood.

as the total number of institutions was declining, banking competition in both metropolitan and rural areas was actually starting to increase.


As of Aug. 30, 2007, Federal Reserve Notes are concentrated in 1) New York, 2) San Francisco, 3) Atlanta, 4) Richmond, & 5) Chicago (H.41 release).

The 5 largest cities have $ 582,795 out of $ 775,186 Federal Reserve Notes (in millions), or 62% of the total deposits.

As of Mar. 3, 2005, the 5 largest cities have $ 534,781 out of $ 717,152, or 75% of total deposits.

As the data shows, Federal Reserve Notes have circulated away from money center banks in the last 2 years. Maybe there would be a lending correlation if I had the geographic distribution on the where-abouts of the number of small companies. Just playing.

[Finster]

Calling Lukester

Heeellllllllppp!!!

[bart]

Re: Calling Lukester

Heeellllllllppp!!!

Rough translation:

1. Less banks since the S&L crisis in the early '90s
2. More branches of existing banks also, and mostly due to more lax regulations. Less S&Ls due to regulation changes too.
3. Both trends show signs of slowing.
4. More cash is apparently being held by folk outside major cities as a percentage of the whole in the last 2-3 years.


And if that isn't enough:



http://www.nowandfutures.com/grins/mmm_something.wav ;)

[Guest]

Re: Inflation Peaks/Real-gdp Peaks/Interest Rates Peak

Finster -

Here's what I figure -

A) Flow5 is unstoppable - this thread will lengthen until it drops through your desk, through the floor, through the sub-floor, through the neighbors kitchen downstairs, through the basement and into the ground on it's way to the CORE - FLOW5 is the element LEAD (PB) - you must step aside or be crushed by the lava FLOW-ing.

B) In our present predicament a half dozen Prozac's are as good a countermove to the crisis as anything else, so that's a better bet than tangling with Flow5.

C) I'm all tuckered out from debating Chris Coles over on the 'Backing up the Truck' thread where I've made the usual pain in the ass out of myself.

D) Tet is coming after me with a rusty saw toothed machete right now and I've got to run for my life. (I think he wants to string me up, and Metalman swore he was gonna help get the job done)

E) I'm betting "inflation peaks" will keep going, and keep going, and keep going, like the energizer bunny. Aoogggha ! It's a runaway train !!!!!!!!

[c1ue]

Re: Inflation Peaks/Real-gdp Peaks/Interest Rates Peak

Flow5,

Good information.

How does my view that 75% of all small businesses are really tax shelters fit into your equation?

Note that this view is not just tin foil hat me, many of the accountants I have worked with share this same view (7 at last count).

It is amazing what can be written off once you have a business cash flow.

[flow5]

Re: Inflation Peaks/Real-gdp Peaks/Interest Rates Peak

I was told that currently, loans were being denied to small businesses & that this would accelerate any downswing.

As far as tax shelters, that's out of my league.

by Prieur du Plessis


The chart below, courtesy of Chart of the Day...the strongest upward movement in stocks has historically occurred during the November to January period, September has proven to be the most difficult month for stocks. click to enlarge

[flow5]

Re: Inflation Peaks/Real-gdp Peaks/Interest Rates Peak

DATA as of 07/01/07 --- no sign of trouble yet:

(1) Total commercial bank credit is growing at c. 9% annual rate (down from c. 10% in 2006).
(2) Total Commercial & Industrial loans are growing at c. 12% annual rate (down from c. 13% in 2006).
(3) Total commercial bank investments are growing at c. 5% annual rate (up from c. 4% in 2006).

(4) Total commercial bank held U.S. government securities falling at c. -3% annual rate (fell from +6% on 11/01/06).
(5) Total commercial bank held "other securities" are growing at c. 15% annual rate (up from +13% in 2006).
(6) Total consumer credit is growing at c. 5% annual rate (2006-present).