Fixing the issue in assumption of OLS step by step or one by one
Recent newsHi, I want to raise the issue related to know whether your OLS is ok or not.
read more(Comments)
by DM
Learn things especially in coding need a practice. Lets put it into work then. Today we are going to enthusiatly dig deeper between what is VAR and what is structural VAR.Quote
PhD is when you are trying to explain something and get so enthusiatly love about it.
Var or vector autoregression or unstructured vector autoregression is a way of learning the relationship between one variable without structural limitations such as time. However, the problem with VAR is that sometimes there is no particular rule on seeing both data related to each other. For example, in monetary policy, let's say we want to control the inflation of the price; as we expect inflation to rise, the monetary authority will increase its instrument and the interest rate and expect the commodity price to go down. It turns out that the price is not going down; instead, it is rising. Then, without any rule in conclusion, opening the tide of economic mystery, we will conclude that raising the interest rate will also increase inflation or commodity prices.
Learn in the video below.
Meanwhile, structural vector autoregression is similar to vector autoregression but with many more constraints, for example, time. One of the differences is in the sample. For example, the government attempted to reduce inflation by increasing the interest rate. In the unstructured vector autoregression, when increasing the interest rate rises inflation, we just read it as it is, which will create an erroneous conclusion. Meanwhile, in structure vector autoregression, we have a time duration that can help explain when the price increases, in which period the inflation goes down or starts to take effect, and whether it's significant.
Here, I found a couple of great videos about SVAR
1. Why SVAR
Svar is a fascinating development in macroeconomics from Christopher Sims. From this video, for example, when the bank anticipates inflation while buying releases more money, the inflation still rises. The wrong conclusion is that the interest rate hike led to inflation. But the monetary policy is an endogenous reaction to expected inflation. The same issue occurred with fiscal policy; for example, we expect that there will be a reduction in private demand and, therefore, an increase in public spending, and the output will still decline. The wrong conclusion is that public spending will cause the work to fall. However, fiscal policy reacted endogenously with the reduction in production. To measure the effect of policy, we need to identify or isolate purely exogenous independent movements and how the economy reacts to them. It is called impulse reaction.  Therefore, we need to identify the structural model that isolates the exogenous variable from the model. After the shock hits the economy, getting the structural model is called identification. According to Sims (1986), Identification is the interpretation of historically observed variation in data in a way that allows the variation to be used to predict the consequences of an action not yet undertaken. After the structure is identified, one can predict inflation and output growth. And we can expect the fiscal effect on GDP.
2. The calculation behind SVAR
ok
How to identify purely exogenous shock
Let's say we have
\[ AX_t = \beta_0+\beta X_{t-1} + u_t \]
From the explanation above, the vector \( X \) relies on its lag itself and structural shock \[ u \].
if we assume that X has 2 variables, which is GDP gap y and interest rate r: it become
\[ X_t = \begin{bmatrix} y \\ r\end{bmatrix} \]
and make the system become
\[ \begin{matrix} y_t + a_{12} r_t = \beta_{10}+\beta_{11} y_{t-1}+\beta_{12} r_{t-1}+ u_{yt} \\a_{21} y_t + r_t = \beta_{20}+\beta_{21} y_{t-1}+\beta_{22}r_{t-1}+ u_{rt} \end{matrix} \]
Where it can be written in matrix form
\[ \begin{bmatrix} 1 & a_{12} \\ a_{21} & 1 \end{bmatrix} \begin{bmatrix} y_t \\ r_t \end{bmatrix} = \begin{bmatrix} \beta_{10} \\ \beta_{20} \end{bmatrix} \begin{bmatrix} \beta_{11} & \beta_{12} \\ \beta_{21} & \beta_{22}\end{bmatrix} \begin{bmatrix} y_{t-1} \\ r_{t-1} \end{bmatrix} +\begin{bmatrix} u_{yt} \\ u_{rt} \end{bmatrix} \]
where
\[ A = \begin{bmatrix} 1 & a_{12} \\ a_{21} & 1 \end{bmatrix} \]
What are identity matrices? Check this video also
And also, what is inverse matrices
How to find inverse matrix
Test the matrix
In Matrix A, the constants 1 and 1 show a contemporary relationship.
\[ \begin{matrix} 1 & 2 & 3 \\ a & b & c \end{matrix} \]
test the matrix
\[ \begin{bmatrix} 1 & 2 & 3 \\ a & b & c \end{bmatrix} \]
\[ \begin{bmatrix} 1 & 2 & 3 \\ a & b & c \end{bmatrix} \]
3.
what is a structural var |
var and svar in market risk |
library vars |
svar model in r |
var vs svar risk |
svar model example |
var in stata |
vars package in r |
thanks
Reference
Dąbrowski, M.A., Widiantoro, D.M. Effectiveness and conduct of macroprudential policy in Indonesia in 2003–2020: Evidence from the structural VAR models. Eurasian Econ Rev 13, 703–731 (2023). https://doi.org/10.1007/s40822-023-00244-w
Hi, I want to raise the issue related to know whether your OLS is ok or not.
read moreThe **45-degree line** in economics and geometry refers to a line where the values on the x-axis and y-axis are equal at every point. It typically has a slope of 1, meaning that for every unit increase along the horizontal axis (x), there is an equal unit increase along the vertical axis (y). Here are a couple of contexts where the 45-degree line is significant:
read moreThe **hyperinflation in Hungary** in the aftermath of World War II (1945–1946) is considered the worst case of hyperinflation in recorded history. The reasons behind this extreme economic event are numerous, involving a combination of war-related devastation, political instability, massive fiscal imbalances, and mismanagement of monetary policy. Here's an in-depth look at the primary causes:
read more**Neutrality of money** is a concept in economics that suggests changes in the **money supply** only affect **nominal variables** (like prices, wages, and exchange rates) and have **no effect on real variables** (like real GDP, employment, or real consumption) in the **long run**.
read moreDeflation in Japan, which has persisted over several decades since the early 1990s, is a complex economic phenomenon. It has been influenced by a combination of structural, demographic, monetary, and fiscal factors. Here are the key reasons why deflation occurred and persisted in Japan:
read moreHedging against inflation involves taking financial or investment actions designed to protect the purchasing power of money in the face of rising prices. Inflation erodes the value of currency over time, so investors seek assets or strategies that tend to increase in value or generate returns that outpace inflation. Below are several ways to hedge against inflation:
read moreThe **Phillips Curve** illustrates the relationship between inflation and unemployment, and how this relationship differs in the **short run** and the **long run**. Over time, economists have modified the original Phillips Curve framework to reflect more nuanced understandings of inflation and unemployment dynamics.
read moreDealing with inflation requires a combination of **fiscal and monetary policy** tools. Policymakers adjust these tools depending on the nature of inflation—whether it's **demand-pull** (inflation caused by excessive demand in the economy) or **cost-push** (inflation caused by rising production costs). Below are key approaches to controlling inflation through fiscal and monetary policy.
read moreCollaboratively administrate empowered markets via plug-and-play networks. Dynamically procrastinate B2C users after installed base benefits. Dramatically visualize customer directed convergence without
Comments