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In economics, gross output (GO) is the measure of total economic activity in the production of new goods and services in an accounting period. It is a much broader measure of the economy than gross domestic product (GDP), which is limited mainly to final output (finished goods and services). As of first-quarter 2019, the Bureau of Economic Analysis estimated gross output in the United States to be 21.1 trillion for GDP. GO is defined by the Bureau of Economic Analysis (BEA) as "a measure of an industry's sales or receipts, which can include sales to final users in the economy (GDP) or sales to other industries (intermediate inputs). Gross output can also be measured as the sum of an industry's value added and intermediate inputs." It is equal to the value of net output or GDP (also known as gross value added) plus intermediate consumption. Gross output represents, roughly speaking, the total value of sales by producing enterprises (their turnover) in an accounting period (e.g. a quarter or a year), before subtracting the value of intermediate goods used up in production. Starting in April 2014, the BEA began publishing gross output and gross output-by-industry on a quarterly basis, along with GDP. Economists regard GO and GDP as complementary aggregate measures of the economy. Many analysts view GO as a more comprehensive way to analyze the economy and the business cycle. "Gross output [GO] is the natural measure of the production sector, while net output [GDP] is appropriate as a measure of welfare. Both are required in a complete system of accounts." In his work, The Purchasing Power of Money: Its Determination and Relation to Credit, Interest, and Crises (1911, 1920), Yale professor Irving Fisher introduced a theoretical measure of "volume of trade" with his equation of exchange: MV = PT, where PT measured the "volume of trade" in the economy at a specified time. In 1931, Friedrich A. Hayek, the Austrian economist at the London School of Economics, created a diagram known as Hayek's triangles as a theoretical measure of the stages of production.
[2]Paolo Prandoni, [3]LCAV, EPFL
In this notebook we will implement a simple fractional resampler that
uses local Lagrange interpolation. The resampler can be used to perform
any rational sampling rate change (but beware of aliasing when
downsampling!)
In [1]:
import numpy as np
import IPython
from scipy.io import wavfile
Local Lagrange interpolation[4]¶
To perform resampling we will need to compute subsample values and, in [2]Paolo Prandoni, [3]LCAV, EPFL
In [1]:
import matplotlib.pyplot as plt
import numpy as np
import scipy.signal as sp
import seaborn as sns
sns.set()
In [2]:
plt.rcParams["figure.figsize"] = (14,4)
The basic reproduction number[4]¶
The propagation mechanism of an epidemic such as the one caused by
SARS-CoV-2 virus can be roughly modeled, at least in its inital phase,
as a process in which each infected individShift + Enter or Ctr + Enter.
As the variables contained in a cell are stor [2]Paolo Prandoni, [3]LCAV, EPFL
In this notebook we will explore various ways to implement a system
that changes the voice of a speaker. Typical applications for these
techniques, strictly sorted by plausibility, include international spy
missions and prank telephone calls, and devices such as the one
displayed here can be easily bought on the web... or in a novelty shop.
No description has been provided for t