{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## State space models - Chandrasekhar recursions" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "execution": { "iopub.execute_input": "2026-07-29T17:41:17.271784Z", "iopub.status.busy": "2026-07-29T17:41:17.271564Z", "iopub.status.idle": "2026-07-29T17:41:21.222606Z", "shell.execute_reply": "2026-07-29T17:41:21.219612Z" } }, "outputs": [], "source": [ "%matplotlib inline\n", "\n", "import numpy as np\n", "import pandas as pd\n", "\n", "import statsmodels.api as sm" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Although most operations related to state space models rely on the Kalman filtering recursions, in some special cases one can use a separate method often called \"Chandrasekhar recursions\". These provide an alternative way to iteratively compute the conditional moments of the state vector, and in some cases they can be substantially less computationally intensive than the Kalman filter recursions. For complete details, see the paper \"Using the 'Chandrasekhar Recursions' for Likelihood Evaluation of DSGE Models\" (Herbst, 2015). Here we just sketch the basic idea." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### State space models and the Kalman filter\n", "\n", "Recall that a time-invariant state space model can be written:\n", "\n", "$$\n", "\\begin{aligned}\n", "y_t &= Z \\alpha_t + \\varepsilon_t, \\qquad \\varepsilon_t \\sim N(0, H) \\\\\n", "\\alpha_{t+1} & = T \\alpha_t + R \\eta_t, \\qquad \\eta_t \\sim N(0, Q) \\\\\n", "\\alpha_1 & \\sim N(a_1, P_1)\n", "\\end{aligned}\n", "$$\n", "\n", "where $y_t$ is a $p \\times 1$ vector and $\\alpha_t$ is an $m \\times 1$ vector.\n", "\n", "Each iteration of the Kalman filter, say at time $t$, can be split into three parts:\n", "\n", "1. **Initialization**: specification of $a_t$ and $P_t$ that define the conditional state distribution, $\\alpha_t \\mid y^{t-1} \\sim N(a_t, P_t)$.\n", "2. **Updating**: computation of $a_{t|t}$ and $P_{t|t}$ that define the conditional state distribution, $\\alpha_t \\mid y^{t} \\sim N(a_{t|t}, P_{t|t})$.\n", "3. **Prediction**: computation of $a_{t+1}$ and $P_{t+1}$ that define the conditional state distribution, $\\alpha_{t+1} \\mid y^{t} \\sim N(a_{t+1}, P_{t+1})$.\n", "\n", "Of course after the first iteration, the prediction part supplies the values required for initialization of the next step." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Focusing on the prediction step, the Kalman filter recursions yield:\n", "\n", "$$\n", "\\begin{aligned}\n", "a_{t+1} & = T a_{t|t} \\\\\n", "P_{t+1} & = T P_{t|t} T' + R Q R' \\\\\n", "\\end{aligned}\n", "$$\n", "\n", "where the matrices $T$ and $P_{t|t}$ are each $m \\times m$, where $m$ is the size of the state vector $\\alpha$. In some cases, the state vector can become extremely large, which can imply that the matrix multiplications required to produce $P_{t+1}$ can be become computationally intensive." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Example: seasonal autoregression\n", "\n", "As an example, notice that an AR(r) model (we use $r$ here since we already used $p$ as the dimension of the observation vector) can be put into state space form as:\n", "\n", "$$\n", "\\begin{aligned}\n", "y_t &= \\alpha_t \\\\\n", "\\alpha_{t+1} & = T \\alpha_t + R \\eta_t, \\qquad \\eta_t \\sim N(0, Q)\n", "\\end{aligned}\n", "$$\n", "\n", "where:\n", "\n", "\n", "$$\n", "\\begin{aligned}\n", "T = \\begin{bmatrix}\n", "\\phi_1 & \\phi_2 & \\dots & \\phi_r \\\\\n", "1 & 0 & & 0 \\\\\n", "\\vdots & \\ddots & & \\vdots \\\\\n", "0 & & 1 & 0 \\\\\n", "\\end{bmatrix} \\qquad\n", "R = \\begin{bmatrix}\n", "1 \\\\\n", "0 \\\\\n", "\\vdots \\\\\n", "0\n", "\\end{bmatrix} \\qquad\n", "Q = \\begin{bmatrix}\n", "\\sigma^2\n", "\\end{bmatrix}\n", "\\end{aligned}\n", "$$\n", "\n", "In an AR model with daily data that exhibits annual seasonality, we might want to fit a model that incorporates lags up to $r=365$, in which case the state vector would be at least $m = 365$. The matrices $T$ and $P_{t|t}$ then each have $365^2 = 133225$ elements, and so most of the time spent computing the likelihood function (via the Kalman filter) can become dominated by the matrix multiplications in the prediction step." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### State space models and the Chandrasekhar recursions\n", "\n", "The Chandrasekhar recursions replace equation $P_{t+1} = T P_{t|t} T' + R Q R'$ with a different recursion:\n", "\n", "$$\n", "P_{t+1} = P_t + W_t M_t W_t'\n", "$$\n", "\n", "but where $W_t$ is a matrix with dimension $m \\times p$ and $M_t$ is a matrix with dimension $p \\times p$, where $p$ is the dimension of the observed vector $y_t$. These matrices themselves have recursive formulations. For more general details and for the formulas for computing $W_t$ and $M_t$, see Herbst (2015).\n", "\n", "**Important note**: unlike the Kalman filter, the Chandrasekhar recursions can not be used for every state space model. In particular, the latter has the following restrictions (that are not required for the use of the former):\n", "\n", "- The model must be time-invariant, except that time-varying intercepts are permitted.\n", "- Stationary initialization of the state vector must be used (this rules out all models in non-stationary components)\n", "- Missing data is not permitted" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To understand why this formula can imply more efficient computations, consider again the SARIMAX case, above. In this case, $p = 1$, so that $M_t$ is a scalar and we can rewrite the Chandrasekhar recursion as:\n", "\n", "$$\n", "P_{t+1} = P_t + M_t \\times W_t W_t'\n", "$$\n", "\n", "The matrices being multiplied, $W_t$, are then of dimension $m \\times 1$, and in the case $r=365$, they each only have $365$ elements, rather than $365^2$ elements. This implies substantially fewer computations are required to complete the prediction step." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Convergence\n", "\n", "A factor that complicates a straightforward discussion of performance implications is the well-known fact that in time-invariant models, the predicted state covariance matrix will converge to a constant matrix. This implies that there exists an $S$ such that, for every $t > S$, $P_t = P_{t+1}$. Once convergence has been achieved, we can eliminate the equation for $P_{t+1}$ from the prediction step altogether.\n", "\n", "In simple time series models, like AR(r) models, convergence is achieved fairly quickly, and this can limit the performance benefit to using the Chandrasekhar recursions. Herbst (2015) focuses instead on DSGE (Dynamic Stochastic General Equilibrium) models instead, which often have a large state vector and often a large number of periods to achieve convergence. In these cases, the performance gains can be quite substantial." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Practical example\n", "\n", "As a practical example, we will consider monthly data that has a clear seasonal component. In this case, we look at the inflation rate of apparel, as measured by the consumer price index. A graph of the data indicates strong seasonality." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2026-07-29T17:41:21.225368Z", "iopub.status.busy": "2026-07-29T17:41:21.224832Z", "iopub.status.idle": "2026-07-29T17:41:22.101549Z", "shell.execute_reply": "2026-07-29T17:41:22.098320Z" } }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "cpi_apparel = pd.read_csv(\n", " \"https://raw.githubusercontent.com/statsmodels/smdatasets/refs/heads/main/data/statespace-chandrasekhar/CPIAPPNS.csv\",\n", " index_col=0,\n", " parse_dates=True,\n", ")\n", "cpi_apparel.index.freq = cpi_apparel.index.inferred_freq\n", "inf_apparel = np.log(cpi_apparel).diff().iloc[1:] * 1200\n", "_ = inf_apparel.plot(figsize=(15, 5))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will construct two model instances. The first will be set to use the Kalman filter recursions, while the second will be set to use the Chandrasekhar recursions. This setting is controlled by the `ssm.filter_chandrasekhar` property, as shown below.\n", "\n", "The model we have in mind is a seasonal autoregression, where we include the first 6 months as lags as well as the given month in each of the previous 15 years as lags. This implies that the state vector has dimension $m = 186$, which is large enough that we might expect to see some substantial performance gains by using the Chandrasekhar recursions.\n", "\n", "**Remark**: We set `tolerance=0` in each model - this has the effect of preventing the filter from ever recognizing that the prediction covariance matrix has converged. *This is not recommended in practice*. We do this here to highlight the superior performance of the Chandrasekhar recursions when they are used in every period instead of the typical Kalman filter recursions. Later, we will show the performance in a more realistic setting that we do allow for convergence." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2026-07-29T17:41:22.117269Z", "iopub.status.busy": "2026-07-29T17:41:22.116876Z", "iopub.status.idle": "2026-07-29T17:41:22.140377Z", "shell.execute_reply": "2026-07-29T17:41:22.139312Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "186\n" ] } ], "source": [ "# Model that will apply Kalman filter recursions\n", "mod_kf = sm.tsa.SARIMAX(\n", " inf_apparel, order=(6, 0, 0), seasonal_order=(15, 0, 0, 12), tolerance=0\n", ")\n", "print(mod_kf.k_states)\n", "\n", "# Model that will apply Chandrasekhar recursions\n", "mod_ch = sm.tsa.SARIMAX(\n", " inf_apparel, order=(6, 0, 0), seasonal_order=(15, 0, 0, 12), tolerance=0\n", ")\n", "mod_ch.ssm.filter_chandrasekhar = True" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We time computation of the log-likelihood function, using the following code:\n", "\n", "```python\n", "%timeit mod_kf.loglike(mod_kf.start_params)\n", "%timeit mod_ch.loglike(mod_ch.start_params)\n", "```\n", "\n", "This results in:\n", "\n", "```\n", "171 ms ± 19.7 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", "85 ms ± 4.97 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", "```\n", "\n", "The implication is that in this experiment, the Chandrasekhar recursions improved performance by about a factor of 2." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As we mentioned above, in the previous experiment we disabled convergence of the predicted covariance matrices, so the results there are an upper bound. Now we allow for convergence, as usual, by removing the `tolerance=0` argument:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2026-07-29T17:41:22.143609Z", "iopub.status.busy": "2026-07-29T17:41:22.143411Z", "iopub.status.idle": "2026-07-29T17:41:22.162941Z", "shell.execute_reply": "2026-07-29T17:41:22.162162Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "186\n" ] } ], "source": [ "# Model that will apply Kalman filter recursions\n", "mod_kf = sm.tsa.SARIMAX(inf_apparel, order=(6, 0, 0), seasonal_order=(15, 0, 0, 12))\n", "print(mod_kf.k_states)\n", "\n", "# Model that will apply Chandrasekhar recursions\n", "mod_ch = sm.tsa.SARIMAX(inf_apparel, order=(6, 0, 0), seasonal_order=(15, 0, 0, 12))\n", "mod_ch.ssm.filter_chandrasekhar = True" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Again, we time computation of the log-likelihood function, using the following code:\n", "\n", "```python\n", "%timeit mod_kf.loglike(mod_kf.start_params)\n", "%timeit mod_ch.loglike(mod_ch.start_params)\n", "```\n", "\n", "This results in:\n", "\n", "```\n", "114 ms ± 7.64 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", "70.5 ms ± 2.43 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", "```\n", "\n", "The Chandrasekhar recursions still improve performance, but now only by about 33%. The reason for this is that after convergence, we no longer need to compute the predicted covariance matrices, so that for those post-convergence periods, there will be no difference in computation time between the two approaches. Below we check the period in which convergence was achieved:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2026-07-29T17:41:22.165940Z", "iopub.status.busy": "2026-07-29T17:41:22.165745Z", "iopub.status.idle": "2026-07-29T17:41:35.127352Z", "shell.execute_reply": "2026-07-29T17:41:35.126354Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Convergence at t=186, of T=469 total observations\n" ] } ], "source": [ "res_kf = mod_kf.filter(mod_kf.start_params)\n", "print(\n", " f\"Convergence at t={res_kf.filter_results.period_converged}, of \"\n", " f\"T={res_kf.nobs} total observations\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Since convergence happened relatively early, we are already avoiding the expensive matrix multiplications in more than half of the periods.\n", "\n", "However, as mentioned above, larger DSGE models may not achieve convergence for most or all of the periods in the sample, and so we could perhaps expect to achieve performance gains more similar to the first example. In their 2019 paper \"Euro area real-time density forecasting with financial or labor market frictions\", McAdam and Warne note that in their applications, \"Compared with the standard Kalman filter, it is our experience that these recursions speed up\n", "the calculation of the log-likelihood for the three models by roughly 50 percent\". This is about the same result as we found in our first example." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Aside on multithreaded matrix algebra routines\n", "\n", "The timings above are based on the Numpy installation installed via Anaconda, which uses Intel's MKL BLAS and LAPACK libraries. These implement multithreaded processing to speed up matrix algebra, which can be particularly helpful for operations on the larger matrices we're working with here. To get a sense of how this affects results, we could turn off multithreading by putting the following in the first cell of this notebook.\n", "\n", "```python\n", "import os\n", "os.environ[\"MKL_NUM_THREADS\"] = \"1\"\n", "```\n", "\n", "When we do this, the timings of the first example change to:\n", "\n", "```\n", "307 ms ± 3.08 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n", "97.5 ms ± 1.64 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", "```\n", "\n", "and the timings of the second example change to:\n", "\n", "```\n", "178 ms ± 2.78 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n", "78.9 ms ± 950 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", "```\n", "\n", "Both are slower, but the typical Kalman filter is affected much more.\n", "\n", "This is not unexpected; the performance differential between single and multithreaded linear algebra is much greater in the typical Kalman filter case, because the whole point of the Chandrasekhar recursions is to reduce the size of the matrix operations. It means that if multithreaded linear algebra is unavailable, the Chandrasekhar recursions offer even greater performance gains." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Chandrasekhar recursions and the univariate filtering approach\n", "\n", "It is also possible to combine the Chandrasekhar recursions with the univariate filtering approach of Koopman and Durbin (2000), by making use of the results of Aknouche and Hamdi in their 2007 paper \"Periodic Chandrasekhar recursions\". An initial implementation of this combination is included in Statsmodels. However, experiments suggest that this tends to degrade performance compared to even the usual Kalman filter. This accords with the computational savings reported for the univariate filtering method, which suggest that savings are highest when the state vector is small relative to the observation vector." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Bibliography\n", "\n", "Aknouche, Abdelhakim, and Fayçal Hamdi. \"Periodic Chandrasekhar recursions.\" arXiv preprint arXiv:0711.3857 (2007).\n", "\n", "Herbst, Edward. \"Using the “Chandrasekhar Recursions” for likelihood evaluation of DSGE models.\" Computational Economics 45, no. 4 (2015): 693-705.\n", "\n", "Koopman, Siem J., and James Durbin. \"Fast filtering and smoothing for multivariate state space models.\" Journal of Time Series Analysis 21, no. 3 (2000): 281-296.\n", "\n", "McAdam, Peter, and Anders Warne. \"Euro area real-time density forecasting with financial or labor market frictions.\" International Journal of Forecasting 35, no. 2 (2019): 580-600." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.14.6" } }, "nbformat": 4, "nbformat_minor": 4 }